diff --git a/cases.csv b/cases.csv
index fa0dc507..c856b1a3 100644
--- a/cases.csv
+++ b/cases.csv
@@ -46,8 +46,8 @@ upgradescen,Exogenous upgrade capital cost specification (see inputs\upgrades).
 retscen,Retirement Scenario,Nuke60RetireYear; Nuke80RetireYear; NukeEarlyRetireYear; NukeRefRetireYear,Nuke80RetireYear,
 supplycurve,Wind and Solar Supply Curves,default; 0; naris; 2018,default,
 uraniumscen,Uranium price scenario,AEO_2025_reference; AEO_2026_baseline,AEO_2026_baseline,
-GSw_Region,Specify column from inputs/userinput/modeled_regions.csv or from {column of hierarchy.csv}/{period-delimited entries to keep from that column},N/A,country/USA,
-GSw_ZoneSet,Set of geospatial zones to use as balancing areas (described in inputs/zones/README.md),^(z48|z54|z69|z132|z134|z3109|UTcounty|PJMcounty)$,z132,
+GSw_Region,Specify {column of hierarchy.csv}/{period-delimited entries to keep from that column},N/A,country/USA,
+GSw_ZoneSet,Set of geospatial zones to use as balancing areas (described in inputs/zones/README.md),^(z48|z54|z69|z90|z132|z134|z3109|UTcounty|PJMcounty)$,z132,
 capcredit_hierarchy_level,Select level at which to aggregate net load for capacity-credit calculation,r; nercr; transreg; transgrp; cendiv; st; interconnect; country; usda_region,transreg,
 construction_schedules_suffix,File suffix for construction schedules,default,default,
 construction_times_suffix,File suffix for construction times by technology,default,default,
diff --git a/docs/source/faq.md b/docs/source/faq.md
index 584a9a4a..df6dc837 100644
--- a/docs/source/faq.md
+++ b/docs/source/faq.md
@@ -59,9 +59,9 @@ Yes, you can configure ReEDS as a single interconnect. Limiting the spatial exte
 
 The ReEDS model is capable of capturing several spatial resolutions. This aspect of the model is controlled by the `GSw_Region` and `GSw_ZoneSet` switches.
 
-- Balancing areas (BAs) and aggregated groups of BAs: Aggregation level is controlled by the 'aggreg' column of the `inputs/zones/GSw_ZoneSet/hierarchy_from134.csv` file.
+- Aggregated groups of counties: Model zone is specified by the 'r' column of the `inputs/zones/GSw_ZoneSet/hierarchy.csv` file.
   - 134 zones: `GSw_ZoneSet = z134`
-  - 132 zones (**default**): `GSw_ZoneSet = z132`. Merges p119 into p122 and p30 into p28.
+  - 132 zones (**default**): `GSw_ZoneSet = z132`. Identical to z134 except merges p119 into p122 and p30 into p28.
   - 69 zones: `GSw_ZoneSet = z69`. Obeys state, interconnect, NERC, and FERC region boundaries; most other zones below these levels are aggregated together.
   - 54 zones: `GSw_ZoneSet = z54`. Obeys state boundaries but nudges the edges of interconnect, NERC, and FERC region boundaries to align with states. Keeps CA, IL, and NY split into 2 zones and TX split into 4 zones.
   - 48 zones: `GSw_ZoneSet = z48`. Obeys state boundaries but nudges the edges of interconnect, NERC, and FERC region boundaries to align with states (highly simplified).
diff --git a/docs/sources.csv b/docs/sources.csv
index e0ca5e3c..b7a953f3 100644
--- a/docs/sources.csv
+++ b/docs/sources.csv
@@ -685,7 +685,6 @@ RelativeFilePath,RelativeFolderPath,FileName_new,FileExtension,Description_new,I
 /inputs/userinput/ivt_default.csv,/inputs/userinput,ivt_default,.csv,,,,,,
 /inputs/userinput/ivt_small.csv,/inputs/userinput,ivt_small,.csv,,,,,,
 /inputs/userinput/ivt_step.csv,/inputs/userinput,ivt_step,.csv,ivt steps for endyears beyond 2050,,,,,
-/inputs/userinput/modeled_regions.csv,/inputs/userinput,modeled_regions,.csv,Sets of BA regions that a user can model in a run. Each column is a different region option and can be specified in cases using GSw_Region.,,,,,
 /inputs/userinput/windows_2100.csv,/inputs/userinput,windows_2100,.csv,Window size for using window solve method to 2100,,,,,
 /inputs/userinput/windows_default.csv,/inputs/userinput,windows_default,.csv,Window size for using window solve method,,,,,
 /inputs/userinput/windows_step10.csv,/inputs/userinput,windows_step10,.csv,Window size for beyond2050step10,,,,,
diff --git a/docs/sources_documentation.md b/docs/sources_documentation.md
index 21237a2e..08c91a21 100644
--- a/docs/sources_documentation.md
+++ b/docs/sources_documentation.md
@@ -3434,10 +3434,6 @@
     - **Description:** ivt steps for endyears beyond 2050
 ---
 
-  - [modeled_regions.csv](/inputs/userinput/modeled_regions.csv)
-    - **Description:** Sets of BA regions that a user can model in a run. Each column is a different region option and can be specified in cases using GSw_Region.
----
-
   - [windows_2100.csv](/inputs/userinput/windows_2100.csv)
     - **Description:** Window size for using window solve method to 2100
 ---
diff --git a/hourlize/qaqc/summarize_supply_curves.py b/hourlize/qaqc/summarize_supply_curves.py
index 4522abcf..e1f864b6 100644
--- a/hourlize/qaqc/summarize_supply_curves.py
+++ b/hourlize/qaqc/summarize_supply_curves.py
@@ -83,8 +83,6 @@ def load_raw_supply_curves(rev_paths):
     args = parser.parse_args()
     rev_paths_files = args.rev_paths
     techs = args.techs
-    # only summarize ba supply curves for now
-    resolution = {'GSw_RegionResolution': 'ba'}
 
     ## set paths
     hourlize_path = os.path.dirname(os.path.realpath(__file__))
@@ -105,7 +103,7 @@ def load_raw_supply_curves(rev_paths):
             sys.exit(1)
         else:
             rev_path = pd.read_csv(rp)
-            rev_path = runreeds.get_rev_paths(rev_path, resolution)
+            rev_path = runreeds.get_rev_paths(rev_path)
             # subset to base name for sc_path
             rev_path['sc_folder'] = rev_path['sc_path'].apply(lambda row: os.path.basename(row))
             # subset to relevant columns and techs
diff --git a/hourlize/reeds_to_rev.py b/hourlize/reeds_to_rev.py
index 38be1570..196b3d71 100644
--- a/hourlize/reeds_to_rev.py
+++ b/hourlize/reeds_to_rev.py
@@ -217,22 +217,13 @@ def reaggregate_supply_curve_regions(df_sc_in, run_folder):
         ``df_sc_in`` where values of "region" are remapped to aggregated regions.
         If not, returns ``df_sc_in`` unchanged.
     """
-    sw = reeds.io.get_switches(run_folder)
-    if sw["GSw_RegionResolution"] == "county":
-        ### Map original sc regions to county
-        # pylint: disable-next=consider-using-f-string
-        df_sc_in["region"] = "p" + df_sc_in.FIPS.astype(str).map("{:>05}".format)
-
-    elif sw["GSw_RegionResolution"] == "aggreg":
-        ### Load  hierarchy file
-        hierarchy = pd.read_csv(
-            os.path.join(run_folder, "inputs_case", "hierarchy_original.csv"),
-            index_col="ba",
-        )
-        if "aggreg" in hierarchy.columns:
-            r2aggreg = hierarchy.aggreg.copy()
-            ### Map original regions to new aggreg's
-            df_sc_in["region"] = df_sc_in["region"].map(r2aggreg)
+    county2zone = reeds.io.get_county2zone(run_folder)
+    df_sc_in["region"] = (
+        df_sc_in.FIPS
+        .astype(str)
+        .map("{:>05}".format)
+        .map(county2zone)
+    )
 
     return df_sc_in
 
diff --git a/inputs/disaggregation/disagg_hydroexist.csv b/inputs/disaggregation/disagg_hydroexist.csv
index 7d604669..01fe031a 100644
--- a/inputs/disaggregation/disagg_hydroexist.csv
+++ b/inputs/disaggregation/disagg_hydroexist.csv
@@ -1,4 +1,4 @@
-PCA_REG,FIPS,i,fracdata
+legacy_ba,FIPS,i,fracdata
 p1,p53007,hydUD,0.16290661070304302
 p1,p53033,hydUD,0.03384050367261281
 p1,p53057,hydUD,0.2759706190975865
diff --git a/inputs/userinput/futurefiles.csv b/inputs/userinput/futurefiles.csv
index 5ce71c1b..4baf6300 100644
--- a/inputs/userinput/futurefiles.csv
+++ b/inputs/userinput/futurefiles.csv
@@ -2,7 +2,6 @@ filename,filetype,ignore,key,year_col,fix_cols,wide,header,forecast_fit,clip_min
 aclike.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 acp_disallowed.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 acp_prices.csv,.csv,0,None,wide,st,1,0,constant,None,None,done,constant
-agglevels.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 allout_RSC.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 allt.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 alpha.csv,.csv,0,None,t,None,1,0,constant,None,None,done,linear_10
@@ -198,7 +197,6 @@ heat_rate_penalty_spin.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,
 heat_rate.csv,.csv,0,None,t,"i,v,r",0,0,constant,0,None,done,constant
 hierarchy_itlgrp.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 hierarchy_original.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
-hierarchy_with_res.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 hierarchy.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 hintage_char.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 hintage_data.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
@@ -256,7 +254,6 @@ min_retire_age.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 minCF.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 mingen_fixed.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 minloadfrac0.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
-modeled_regions.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 modeledyears.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 month.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 month2quarter.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
@@ -364,7 +361,6 @@ pvbcapcostmult.csv,.csv,0,None,t,None,0,0,constant,None,None,done,constant
 pvf_cap.csv,.csv,1,None,*t,None,0,0,linear_5,0,None,done (but double-check that it is written correctly by calc_financial_inputs.py),linear_5
 pvf_onm_int.csv,.csv,1,None,*t,None,0,0,linear_10,0,None,done (but double-check that it is written correctly by calc_financial_inputs.py),linear_10
 quarter.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
-r_ba.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 r_cendiv.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 r_county.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 r_cs_distance_mi.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
@@ -479,8 +475,6 @@ upgrade_mult_mid.csv,.csv,0,None,wide,dummy,1,0,linear_5,0,None,new,
 upgradelink_water.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
 uranium_price.csv,.csv,0,None,year,None,0,0,linear_5,0,None,new,
 va_ng_crf_penalty.csv,.csv,0,None,0,None,0,None,constant,None,None,done,constant
-val_ba.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
-county.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 val_cs.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 val_r_all.csv,.csv,1,None,9999,None,9999,0,constant,None,None,new,
 var_map.csv,.csv,1,None,9999,None,9999,0,constant,None,None,done,constant
diff --git a/inputs/userinput/modeled_regions.csv b/inputs/userinput/modeled_regions.csv
deleted file mode 100644
index 137a6662..00000000
--- a/inputs/userinput/modeled_regions.csv
+++ /dev/null
@@ -1,135 +0,0 @@
-r,PJMcounty,UTcounty
-p1,ba,aggreg
-p2,ba,aggreg
-p3,ba,aggreg
-p4,ba,aggreg
-p5,ba,aggreg
-p6,ba,aggreg
-p7,ba,aggreg
-p8,ba,aggreg
-p9,ba,aggreg
-p10,ba,aggreg
-p11,ba,aggreg
-p12,ba,aggreg
-p13,ba,aggreg
-p14,ba,aggreg
-p15,ba,aggreg
-p16,ba,aggreg
-p17,ba,aggreg
-p18,ba,aggreg
-p19,ba,aggreg
-p20,ba,aggreg
-p21,ba,aggreg
-p22,ba,aggreg
-p23,ba,aggreg
-p24,ba,aggreg
-p25,ba,county
-p26,ba,county
-p27,ba,aggreg
-p28,ba,aggreg
-p29,ba,aggreg
-p30,ba,aggreg
-p31,ba,aggreg
-p32,ba,aggreg
-p33,ba,aggreg
-p34,ba,aggreg
-p35,ba,aggreg
-p36,ba,aggreg
-p37,ba,aggreg
-p38,ba,aggreg
-p39,ba,aggreg
-p40,ba,aggreg
-p41,ba,aggreg
-p42,ba,aggreg
-p43,ba,aggreg
-p44,ba,aggreg
-p45,county,aggreg
-p46,county,aggreg
-p47,ba,aggreg
-p48,ba,aggreg
-p49,ba,aggreg
-p50,ba,aggreg
-p51,ba,aggreg
-p52,ba,aggreg
-p53,ba,aggreg
-p54,ba,aggreg
-p55,ba,aggreg
-p56,ba,aggreg
-p57,ba,aggreg
-p58,ba,aggreg
-p59,ba,aggreg
-p60,ba,aggreg
-p61,ba,aggreg
-p62,ba,aggreg
-p63,ba,aggreg
-p64,ba,aggreg
-p65,ba,aggreg
-p66,ba,aggreg
-p67,ba,aggreg
-p68,ba,aggreg
-p69,county,aggreg
-p70,county,aggreg
-p71,ba,aggreg
-p72,ba,aggreg
-p73,ba,aggreg
-p74,county,aggreg
-p75,county,aggreg
-p76,county,aggreg
-p77,county,aggreg
-p78,county,aggreg
-p79,county,aggreg
-p80,county,aggreg
-p81,county,aggreg
-p82,county,aggreg
-p83,county,aggreg
-p84,ba,aggreg
-p85,ba,aggreg
-p86,ba,aggreg
-p87,ba,aggreg
-p88,ba,aggreg
-p89,ba,aggreg
-p90,ba,aggreg
-p91,ba,aggreg
-p92,county,aggreg
-p93,county,aggreg
-p94,ba,aggreg
-p95,ba,aggreg
-p96,ba,aggreg
-p97,county,aggreg
-p98,county,aggreg
-p99,county,aggreg
-p100,county,aggreg
-p101,ba,aggreg
-p102,ba,aggreg
-p103,county,aggreg
-p104,county,aggreg
-p105,county,aggreg
-p106,county,aggreg
-p107,county,aggreg
-p108,county,aggreg
-p109,county,aggreg
-p110,county,aggreg
-p111,county,aggreg
-p112,county,aggreg
-p113,county,aggreg
-p114,county,aggreg
-p115,county,aggreg
-p116,county,aggreg
-p117,county,aggreg
-p118,county,aggreg
-p119,county,aggreg
-p120,county,aggreg
-p121,county,aggreg
-p122,county,aggreg
-p123,county,aggreg
-p124,county,aggreg
-p125,county,aggreg
-p126,county,aggreg
-p127,county,aggreg
-p128,county,aggreg
-p129,ba,aggreg
-p130,ba,aggreg
-p131,ba,aggreg
-p132,ba,aggreg
-p133,ba,aggreg
-p134,ba,aggreg
diff --git a/inputs/zones/PJMcounty/hierarchy_from134.csv b/inputs/zones/PJMcounty/hierarchy_from134.csv
deleted file mode 100644
index c1b5a1a7..00000000
--- a/inputs/zones/PJMcounty/hierarchy_from134.csv
+++ /dev/null
@@ -1,135 +0,0 @@
-ba,nercr,transreg,transgrp,cendiv,st,interconnect,country,usda_region,h2ptcreg,hurdlereg,aggreg
-p1,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Puget_Sound_Energy_Inc,p1
-p2,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,p2
-p3,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Avista_Corp,p3
-p4,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,PUD_No2_of_Grant_County,p4
-p5,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,p5
-p6,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,PacifiCorp_West,p6
-p7,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,p7
-p8,WECC_NW,NorthernGrid,NorthernGrid_South,Pacific,CA,western,USA,pacific,California,PacifiCorp_West,p8
-p9,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,p9
-p10,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,p10
-p11,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,p11
-p12,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,NV,western,USA,mountain,Mountain,Nevada_Power_Co,p12
-p13,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,NV,western,USA,mountain,Mountain,Nevada_Power_Co,p13
-p14,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Avista_Corp,p14
-p15,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,p15
-p16,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,p16
-p17,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p17
-p18,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p18
-p19,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,WAPA_Upper_Great_Plains_West,p19
-p20,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p20
-p21,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,p21
-p22,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,p22
-p23,WECC_NW,WestConnect,WestConnect_North,Mountain,WY,western,USA,mountain,Mountain,WAPA_Rocky_Mountain_Region,p23
-p24,WECC_NW,WestConnect,WestConnect_North,Mountain,WY,western,USA,mountain,Mountain,WAPA_Rocky_Mountain_Region,p24
-p25,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,p25
-p26,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,p26
-p27,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,WAPA_Desert_Southwest_Region,p27
-p28,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,z28
-p29,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,p29
-p30,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,z28
-p31,WECC_SW,WestConnect,WestConnect_South,Mountain,NM,western,USA,mountain,Southwest,Public_Service_Co_of_New_Mexico,p31
-p32,WECC_NW,WestConnect,WestConnect_North,Mountain,SD,western,USA,northern-plains,Plains,WAPA_Rocky_Mountain_Region,p32
-p33,WECC_NW,WestConnect,WestConnect_North,Mountain,CO,western,USA,mountain,Mountain,Public_Service_Co_of_Colorado,p33
-p34,WECC_NW,WestConnect,WestConnect_North,Mountain,CO,western,USA,mountain,Mountain,Public_Service_Co_of_Colorado,p34
-p35,SPP,SPP,SPP_North,West_North_Central,MT,eastern,USA,mountain,Mountain,SPP,p35
-p36,SPP,SPP,SPP_North,West_North_Central,ND,eastern,USA,northern-plains,Plains,SPP,p36
-p37,MISO,MISO,MISO_North,West_North_Central,ND,eastern,USA,northern-plains,Plains,MISO,p37
-p38,SPP,SPP,SPP_North,West_North_Central,SD,eastern,USA,northern-plains,Plains,SPP,p38
-p39,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,p39
-p40,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,p40
-p41,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,p41
-p42,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p42
-p43,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p43
-p44,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p44
-p45,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p45
-p46,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p46
-p47,SPP,SPP,SPP_South,West_South_Central,NM,eastern,USA,mountain,Southwest,SPP,p47
-p48,SPP,SPP,SPP_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,SPP,p48
-p49,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,p49
-p50,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,p50
-p51,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,p51
-p52,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,p52
-p53,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,p53
-p54,SPP,SPP,SPP_South,West_North_Central,MO,eastern,USA,corn-belt,Midwest,SPP,p54
-p55,SPP,SPP,SPP_South,West_North_Central,MO,eastern,USA,corn-belt,Midwest,SPP,p55
-p56,SPP,SPP,SPP_South,West_South_Central,AR,eastern,USA,delta-states,Delta,SPP,p56
-p57,SPP,SPP,SPP_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,SPP,p57
-p58,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,p58
-p59,WECC_SW,WestConnect,WestConnect_South,Mountain,TX,western,USA,southern-plains,Texas,El_Paso_Electric,p59
-p60,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p60
-p61,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p61
-p62,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p62
-p63,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p63
-p64,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p64
-p65,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p65
-p66,MISO,MISO,MISO_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,MISO,p66
-p67,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p67
-p68,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p68
-p69,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p69
-p70,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p70
-p71,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p71
-p72,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p72
-p73,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p73
-p74,MISO,MISO,MISO_North,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,p74
-p75,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p75
-p76,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p76
-p77,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p77
-p78,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p78
-p79,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p79
-p80,PJM,PJM,PJM_West,East_North_Central,IL,eastern,USA,corn-belt,Midwest,PJM,p80
-p81,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p81
-p82,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p82
-p83,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p83
-p84,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p84
-p85,MISO,MISO,MISO_South,West_South_Central,AR,eastern,USA,delta-states,Delta,MISO,p85
-p86,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,p86
-p87,MISO,MISO,MISO_South,East_South_Central,MS,eastern,USA,delta-states,Delta,MISO,p87
-p88,SERC_C,SERTP,SERTP,East_South_Central,MS,eastern,USA,delta-states,Delta,Tennessee_Valley_Authority,p88
-p89,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,Southern_Co_Services_Inc,p89
-p90,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,PowerSouth_Energy_Coop,p90
-p91,SERC_SE,SERTP,SERTP,South_Atlantic,FL,eastern,USA,southeast,Florida,Southern_Co_Services_Inc,p91
-p92,SERC_C,SERTP,SERTP,East_South_Central,TN,eastern,USA,appalachia,Southeast,Tennessee_Valley_Authority,p92
-p93,SERC_C,SERTP,SERTP,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,Tennessee_Valley_Authority,p93
-p94,SERC_SE,SERTP,SERTP,South_Atlantic,GA,eastern,USA,southeast,Southeast,Southern_Co_Services_Inc,p94
-p95,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,Duke_Energy_Carolinas_LLC,p95
-p96,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,South_Carolina_Electric_Gas_Co,p96
-p97,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Carolinas_LLC,p97
-p98,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Progress_East,p98
-p99,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p99
-p100,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p100
-p101,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Seminole_Electric_Coop_Inc,p101
-p102,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Florida_Power_and_Light,p102
-p103,MISO,MISO,MISO_Central,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,p103
-p104,PJM,PJM,PJM_West,East_North_Central,MI,eastern,USA,lake-states,Midwest,PJM,p104
-p105,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,p105
-p106,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,p106
-p107,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,p107
-p108,MISO,MISO,MISO_Central,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,MISO,p108
-p109,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,p109
-p110,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,p110
-p111,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p111
-p112,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p112
-p113,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p113
-p114,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p114
-p115,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,p115
-p116,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,p116
-p117,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,p117
-p118,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p118
-p119,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,z122
-p120,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,p120
-p121,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,p121
-p122,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,z122
-p123,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,p123
-p124,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p124
-p125,PJM,PJM,PJM_East,South_Atlantic,DE,eastern,USA,northeast,MidAtlantic,PJM,p125
-p126,PJM,PJM,PJM_East,Mid_Atlantic,NJ,eastern,USA,northeast,MidAtlantic,PJM,p126
-p127,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,p127
-p128,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,p128
-p129,NPCC_NE,ISONE,ISONE,New_England,VT,eastern,USA,northeast,NewEngland,ISONE,p129
-p130,NPCC_NE,ISONE,ISONE,New_England,NH,eastern,USA,northeast,NewEngland,ISONE,p130
-p131,NPCC_NE,ISONE,ISONE,New_England,MA,eastern,USA,northeast,NewEngland,ISONE,p131
-p132,NPCC_NE,ISONE,ISONE,New_England,CT,eastern,USA,northeast,NewEngland,ISONE,p132
-p133,NPCC_NE,ISONE,ISONE,New_England,RI,eastern,USA,northeast,NewEngland,ISONE,p133
-p134,NPCC_NE,ISONE,ISONE,New_England,ME,eastern,USA,northeast,NewEngland,ISONE,p134
diff --git a/inputs/zones/README.md b/inputs/zones/README.md
index 00fc6295..1a8ea76d 100644
--- a/inputs/zones/README.md
+++ b/inputs/zones/README.md
@@ -6,7 +6,6 @@ Model zones are defined by the following user-generated files:
 - `hierarchy.csv`: Maps from ReEDS zones (`r` column) to the larger region hierarchy levels
 - `b2b.csv`: Back-to-back converter (B2B) capacity [MW] between model zones
 - `newlinks_offshore_radial.csv`: Candiate connections between offshore and coastal land-based zones
-- TEMPORARY 20260402: `hierarchy_from134.csv`: The legacy-formatted `hierarchy.csv` file from the 134-zone version of ReEDS (will be removed once the rest of the spatial input processing is updated)
 
 And the following automatically generated files:
 
@@ -21,6 +20,13 @@ The lat/lon is used for plotting, representative least-cost paths and greenfield
   - If the centroid is NOT within the zone polygon, the node location is the "most interior" point in the polygon
   (determined by iteratively inward-buffering the polygon until it disappears, then keeping the centroid of the penultimate iteration).
 
+
+## Notes on zone options
+
+- `z3109`: 1:1 mapping from counties to zones
+  - Not all counties have high-voltage load buses, so if `GSw_LoadAllocationMethod = state_lpf`, some counties may have zero load.
+
+
 ## Creating a new set of model zones
 
 Start by copying the `county2zone.csv` and `hierarchy.csv` file for an existing set of zones to a new folder (named with a memorable name for your new set of zones) in the [ReEDS_Input_Processing/zones](https://github.com/ReEDS-Model/ReEDS_Input_Processing/tree/main/zones) directory.
@@ -61,6 +67,7 @@ Once you're happy with your zone and hierarchy level definitions, run the follow
     - Creates the `zonehash.csv` file
     - Rewrites the `itl_NARIS.csv`, `transmission_cost_distance.csv`, and `transmission_cost_distance_lines.csv` files
     (existing data in the file are preserved, so you should only see new rows added, typically at the bottom of the file)
+1. If the new zone set requires special processing in ReEDS, add it to the appropriate sections of `inputs/zones/zoneset_config.yaml` (see below)
 1. Add the new zone definition to the choices for the `GSw_ZoneSet` switch in `cases.csv`
 1. To make sure it worked (or just to read the ITLs in general), you can run `import reeds` and then `reeds.inputs.get_itls(GSw_ZoneSet='your new zoneset name')` in Python with the `reeds2` conda environment activated.
 1. Try a ReEDS run.
@@ -82,3 +89,11 @@ The offshore zones are not user-adjustable.
   - `cendiv`: [Census divisions](https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf)
   - `usda_region`: [USDA Farm Production Regions](https://www.ers.usda.gov/data-products/arms-farm-financial-and-crop-production-practices/documentation)
   - `h2ptcreg`: Hydrogen tax credit regions ([DOE 2023, Figure 2](https://www.energy.gov/sites/default/files/2023-12/greet-manual_2023-12-20.pdf))
+
+- `zoneset_config.yaml`: Settings for zoneset-specific processing.
+If `GSw_ZoneSet` is listed beneath one of the following switch names, the described behavior is applied during input processing at the beginning of each ReEDS run using that `GSw_ZoneSet`.
+  - `drop_single_county_reinforcement_cost`: Drop the network reinforcement cost (a component of the interconnection cost) for new wind/solar capacity in single-county zones
+  - `drop_interfaces_missing_cost`: If an AC transmission interface has existing capacity but no expansion cost or representative distance, remove its existing capacity and do not allow it to be expanded.
+  (Turned off for most zone sets because we'd rather stop the run and add the missing data.
+  Turned on for some zone sets with single-county zones that have no high-voltage transmission lines crossing the single-county zone boundaries.)
+  - `reeds2pras_unitsize_unconstrain_counties`: Do not specify max unit sizes using the planning reserve margin (PRM) for single-county zones during ReEDS2PRAS unit disaggregation
diff --git a/inputs/zones/UTcounty/hierarchy_from134.csv b/inputs/zones/UTcounty/hierarchy_from134.csv
deleted file mode 100644
index c1b5a1a7..00000000
--- a/inputs/zones/UTcounty/hierarchy_from134.csv
+++ /dev/null
@@ -1,135 +0,0 @@
-ba,nercr,transreg,transgrp,cendiv,st,interconnect,country,usda_region,h2ptcreg,hurdlereg,aggreg
-p1,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Puget_Sound_Energy_Inc,p1
-p2,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,p2
-p3,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Avista_Corp,p3
-p4,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,PUD_No2_of_Grant_County,p4
-p5,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,p5
-p6,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,PacifiCorp_West,p6
-p7,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,p7
-p8,WECC_NW,NorthernGrid,NorthernGrid_South,Pacific,CA,western,USA,pacific,California,PacifiCorp_West,p8
-p9,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,p9
-p10,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,p10
-p11,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,p11
-p12,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,NV,western,USA,mountain,Mountain,Nevada_Power_Co,p12
-p13,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,NV,western,USA,mountain,Mountain,Nevada_Power_Co,p13
-p14,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Avista_Corp,p14
-p15,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,p15
-p16,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,p16
-p17,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p17
-p18,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p18
-p19,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,WAPA_Upper_Great_Plains_West,p19
-p20,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p20
-p21,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,p21
-p22,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,p22
-p23,WECC_NW,WestConnect,WestConnect_North,Mountain,WY,western,USA,mountain,Mountain,WAPA_Rocky_Mountain_Region,p23
-p24,WECC_NW,WestConnect,WestConnect_North,Mountain,WY,western,USA,mountain,Mountain,WAPA_Rocky_Mountain_Region,p24
-p25,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,p25
-p26,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,p26
-p27,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,WAPA_Desert_Southwest_Region,p27
-p28,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,z28
-p29,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,p29
-p30,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,z28
-p31,WECC_SW,WestConnect,WestConnect_South,Mountain,NM,western,USA,mountain,Southwest,Public_Service_Co_of_New_Mexico,p31
-p32,WECC_NW,WestConnect,WestConnect_North,Mountain,SD,western,USA,northern-plains,Plains,WAPA_Rocky_Mountain_Region,p32
-p33,WECC_NW,WestConnect,WestConnect_North,Mountain,CO,western,USA,mountain,Mountain,Public_Service_Co_of_Colorado,p33
-p34,WECC_NW,WestConnect,WestConnect_North,Mountain,CO,western,USA,mountain,Mountain,Public_Service_Co_of_Colorado,p34
-p35,SPP,SPP,SPP_North,West_North_Central,MT,eastern,USA,mountain,Mountain,SPP,p35
-p36,SPP,SPP,SPP_North,West_North_Central,ND,eastern,USA,northern-plains,Plains,SPP,p36
-p37,MISO,MISO,MISO_North,West_North_Central,ND,eastern,USA,northern-plains,Plains,MISO,p37
-p38,SPP,SPP,SPP_North,West_North_Central,SD,eastern,USA,northern-plains,Plains,SPP,p38
-p39,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,p39
-p40,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,p40
-p41,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,p41
-p42,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p42
-p43,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p43
-p44,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p44
-p45,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p45
-p46,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p46
-p47,SPP,SPP,SPP_South,West_South_Central,NM,eastern,USA,mountain,Southwest,SPP,p47
-p48,SPP,SPP,SPP_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,SPP,p48
-p49,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,p49
-p50,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,p50
-p51,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,p51
-p52,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,p52
-p53,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,p53
-p54,SPP,SPP,SPP_South,West_North_Central,MO,eastern,USA,corn-belt,Midwest,SPP,p54
-p55,SPP,SPP,SPP_South,West_North_Central,MO,eastern,USA,corn-belt,Midwest,SPP,p55
-p56,SPP,SPP,SPP_South,West_South_Central,AR,eastern,USA,delta-states,Delta,SPP,p56
-p57,SPP,SPP,SPP_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,SPP,p57
-p58,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,p58
-p59,WECC_SW,WestConnect,WestConnect_South,Mountain,TX,western,USA,southern-plains,Texas,El_Paso_Electric,p59
-p60,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p60
-p61,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p61
-p62,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p62
-p63,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p63
-p64,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p64
-p65,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p65
-p66,MISO,MISO,MISO_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,MISO,p66
-p67,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p67
-p68,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p68
-p69,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p69
-p70,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p70
-p71,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p71
-p72,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p72
-p73,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p73
-p74,MISO,MISO,MISO_North,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,p74
-p75,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p75
-p76,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p76
-p77,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p77
-p78,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p78
-p79,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p79
-p80,PJM,PJM,PJM_West,East_North_Central,IL,eastern,USA,corn-belt,Midwest,PJM,p80
-p81,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p81
-p82,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p82
-p83,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p83
-p84,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p84
-p85,MISO,MISO,MISO_South,West_South_Central,AR,eastern,USA,delta-states,Delta,MISO,p85
-p86,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,p86
-p87,MISO,MISO,MISO_South,East_South_Central,MS,eastern,USA,delta-states,Delta,MISO,p87
-p88,SERC_C,SERTP,SERTP,East_South_Central,MS,eastern,USA,delta-states,Delta,Tennessee_Valley_Authority,p88
-p89,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,Southern_Co_Services_Inc,p89
-p90,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,PowerSouth_Energy_Coop,p90
-p91,SERC_SE,SERTP,SERTP,South_Atlantic,FL,eastern,USA,southeast,Florida,Southern_Co_Services_Inc,p91
-p92,SERC_C,SERTP,SERTP,East_South_Central,TN,eastern,USA,appalachia,Southeast,Tennessee_Valley_Authority,p92
-p93,SERC_C,SERTP,SERTP,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,Tennessee_Valley_Authority,p93
-p94,SERC_SE,SERTP,SERTP,South_Atlantic,GA,eastern,USA,southeast,Southeast,Southern_Co_Services_Inc,p94
-p95,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,Duke_Energy_Carolinas_LLC,p95
-p96,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,South_Carolina_Electric_Gas_Co,p96
-p97,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Carolinas_LLC,p97
-p98,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Progress_East,p98
-p99,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p99
-p100,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p100
-p101,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Seminole_Electric_Coop_Inc,p101
-p102,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Florida_Power_and_Light,p102
-p103,MISO,MISO,MISO_Central,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,p103
-p104,PJM,PJM,PJM_West,East_North_Central,MI,eastern,USA,lake-states,Midwest,PJM,p104
-p105,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,p105
-p106,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,p106
-p107,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,p107
-p108,MISO,MISO,MISO_Central,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,MISO,p108
-p109,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,p109
-p110,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,p110
-p111,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p111
-p112,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p112
-p113,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p113
-p114,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p114
-p115,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,p115
-p116,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,p116
-p117,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,p117
-p118,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p118
-p119,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,z122
-p120,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,p120
-p121,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,p121
-p122,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,z122
-p123,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,p123
-p124,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p124
-p125,PJM,PJM,PJM_East,South_Atlantic,DE,eastern,USA,northeast,MidAtlantic,PJM,p125
-p126,PJM,PJM,PJM_East,Mid_Atlantic,NJ,eastern,USA,northeast,MidAtlantic,PJM,p126
-p127,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,p127
-p128,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,p128
-p129,NPCC_NE,ISONE,ISONE,New_England,VT,eastern,USA,northeast,NewEngland,ISONE,p129
-p130,NPCC_NE,ISONE,ISONE,New_England,NH,eastern,USA,northeast,NewEngland,ISONE,p130
-p131,NPCC_NE,ISONE,ISONE,New_England,MA,eastern,USA,northeast,NewEngland,ISONE,p131
-p132,NPCC_NE,ISONE,ISONE,New_England,CT,eastern,USA,northeast,NewEngland,ISONE,p132
-p133,NPCC_NE,ISONE,ISONE,New_England,RI,eastern,USA,northeast,NewEngland,ISONE,p133
-p134,NPCC_NE,ISONE,ISONE,New_England,ME,eastern,USA,northeast,NewEngland,ISONE,p134
diff --git a/inputs/zones/hierarchy_offshore.csv b/inputs/zones/hierarchy_offshore.csv
index 4cf66ee4..ba7688e6 100644
--- a/inputs/zones/hierarchy_offshore.csv
+++ b/inputs/zones/hierarchy_offshore.csv
@@ -1,28 +1,28 @@
-ba,nercr,transreg,transgrp,st,interconnect,hurdlereg,aggreg
-oWA,WECC_NW,NorthernGrid,NorthernGrid_West,WA,western,Bonneville_Power_Administration,oWA
-oOR_N,WECC_NW,NorthernGrid,NorthernGrid_West,OR,western,PacifiCorp_West,oOR_N
-oOR_S,WECC_NW,NorthernGrid,NorthernGrid_West,OR,western,PacifiCorp_West,oOR_S
-oCA_NNN,WECC_CA,CAISO,CAISO,CA,western,CAISO,oCA_NNN
-oCA_NN,WECC_CA,CAISO,CAISO,CA,western,CAISO,oCA_NN
-oCA_N,WECC_CA,CAISO,CAISO,CA,western,CAISO,oCA_N
-oCA_S,WECC_CA,CAISO,CAISO,CA,western,CAISO,oCA_S
-oTX,ERCOT,ERCOT,ERCOT,TX,texas,ERCOT,oTX
-oLA,MISO,MISO,MISO_South,LA,eastern,MISO,oLA
-oFL_W,SERC_F,FRCC,FRCC,FL,eastern,Seminole_Electric_Coop_Inc,oFL_W
-oFL_E,SERC_F,FRCC,FRCC,FL,eastern,Seminole_Electric_Coop_Inc,oFL_E
-oSC,SERC_E,SERTP,SERTP,SC,eastern,South_Carolina_Electric_Gas_Co,oSC
-oNC_S,SERC_E,SERTP,SERTP,NC,eastern,Duke_Energy_Progress_East,oNC_S
-oNC_N,SERC_E,SERTP,SERTP,NC,eastern,Duke_Energy_Progress_East,oNC_N
-oVA,PJM,PJM,PJM_East,VA,eastern,PJM,oVA
-oNJ,PJM,PJM,PJM_East,NJ,eastern,PJM,oNJ
-oNY,NPCC_NY,NYISO,NYISO,NY,eastern,NYISO,oNY
-oRI,NPCC_NE,ISONE,ISONE,RI,eastern,ISONE,oRI
-oNH,NPCC_NE,ISONE,ISONE,NH,eastern,ISONE,oNH
-oME,NPCC_NE,ISONE,ISONE,ME,eastern,ISONE,oME
-oMS,MISO,MISO,MISO_South,MS,eastern,MISO,oMS
-oAL,SERC_SE,SERTP,SERTP,AL,eastern,PowerSouth_Energy_Coop,oAL
-oGA,SERC_SE,SERTP,SERTP,GA,eastern,Southern_Co_Services_Inc,oGA
-oMD,PJM,PJM,PJM_East,MD,eastern,PJM,oMD
-oDE,PJM,PJM,PJM_East,DE,eastern,PJM,oDE
-oCT,NPCC_NE,ISONE,ISONE,CT,eastern,ISONE,oCT
-oMA,NPCC_NE,ISONE,ISONE,MA,eastern,ISONE,oMA
+ba,nercr,transreg,transgrp,st,interconnect,hurdlereg
+oWA,WECC_NW,NorthernGrid,NorthernGrid_West,WA,western,Bonneville_Power_Administration
+oOR_N,WECC_NW,NorthernGrid,NorthernGrid_West,OR,western,PacifiCorp_West
+oOR_S,WECC_NW,NorthernGrid,NorthernGrid_West,OR,western,PacifiCorp_West
+oCA_NNN,WECC_CA,CAISO,CAISO,CA,western,CAISO
+oCA_NN,WECC_CA,CAISO,CAISO,CA,western,CAISO
+oCA_N,WECC_CA,CAISO,CAISO,CA,western,CAISO
+oCA_S,WECC_CA,CAISO,CAISO,CA,western,CAISO
+oTX,ERCOT,ERCOT,ERCOT,TX,texas,ERCOT
+oLA,MISO,MISO,MISO_South,LA,eastern,MISO
+oFL_W,SERC_F,FRCC,FRCC,FL,eastern,Seminole_Electric_Coop_Inc
+oFL_E,SERC_F,FRCC,FRCC,FL,eastern,Seminole_Electric_Coop_Inc
+oSC,SERC_E,SERTP,SERTP,SC,eastern,South_Carolina_Electric_Gas_Co
+oNC_S,SERC_E,SERTP,SERTP,NC,eastern,Duke_Energy_Progress_East
+oNC_N,SERC_E,SERTP,SERTP,NC,eastern,Duke_Energy_Progress_East
+oVA,PJM,PJM,PJM_East,VA,eastern,PJM
+oNJ,PJM,PJM,PJM_East,NJ,eastern,PJM
+oNY,NPCC_NY,NYISO,NYISO,NY,eastern,NYISO
+oRI,NPCC_NE,ISONE,ISONE,RI,eastern,ISONE
+oNH,NPCC_NE,ISONE,ISONE,NH,eastern,ISONE
+oME,NPCC_NE,ISONE,ISONE,ME,eastern,ISONE
+oMS,MISO,MISO,MISO_South,MS,eastern,MISO
+oAL,SERC_SE,SERTP,SERTP,AL,eastern,PowerSouth_Energy_Coop
+oGA,SERC_SE,SERTP,SERTP,GA,eastern,Southern_Co_Services_Inc
+oMD,PJM,PJM,PJM_East,MD,eastern,PJM
+oDE,PJM,PJM,PJM_East,DE,eastern,PJM
+oCT,NPCC_NE,ISONE,ISONE,CT,eastern,ISONE
+oMA,NPCC_NE,ISONE,ISONE,MA,eastern,ISONE
diff --git a/inputs/zones/z132/hierarchy_from134.csv b/inputs/zones/z132/hierarchy_from134.csv
deleted file mode 100644
index c1b5a1a7..00000000
--- a/inputs/zones/z132/hierarchy_from134.csv
+++ /dev/null
@@ -1,135 +0,0 @@
-ba,nercr,transreg,transgrp,cendiv,st,interconnect,country,usda_region,h2ptcreg,hurdlereg,aggreg
-p1,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Puget_Sound_Energy_Inc,p1
-p2,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,p2
-p3,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Avista_Corp,p3
-p4,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,PUD_No2_of_Grant_County,p4
-p5,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,p5
-p6,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,PacifiCorp_West,p6
-p7,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,p7
-p8,WECC_NW,NorthernGrid,NorthernGrid_South,Pacific,CA,western,USA,pacific,California,PacifiCorp_West,p8
-p9,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,p9
-p10,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,p10
-p11,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,p11
-p12,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,NV,western,USA,mountain,Mountain,Nevada_Power_Co,p12
-p13,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,NV,western,USA,mountain,Mountain,Nevada_Power_Co,p13
-p14,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Avista_Corp,p14
-p15,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,p15
-p16,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,p16
-p17,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p17
-p18,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p18
-p19,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,WAPA_Upper_Great_Plains_West,p19
-p20,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p20
-p21,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,p21
-p22,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,p22
-p23,WECC_NW,WestConnect,WestConnect_North,Mountain,WY,western,USA,mountain,Mountain,WAPA_Rocky_Mountain_Region,p23
-p24,WECC_NW,WestConnect,WestConnect_North,Mountain,WY,western,USA,mountain,Mountain,WAPA_Rocky_Mountain_Region,p24
-p25,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,p25
-p26,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,p26
-p27,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,WAPA_Desert_Southwest_Region,p27
-p28,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,z28
-p29,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,p29
-p30,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,z28
-p31,WECC_SW,WestConnect,WestConnect_South,Mountain,NM,western,USA,mountain,Southwest,Public_Service_Co_of_New_Mexico,p31
-p32,WECC_NW,WestConnect,WestConnect_North,Mountain,SD,western,USA,northern-plains,Plains,WAPA_Rocky_Mountain_Region,p32
-p33,WECC_NW,WestConnect,WestConnect_North,Mountain,CO,western,USA,mountain,Mountain,Public_Service_Co_of_Colorado,p33
-p34,WECC_NW,WestConnect,WestConnect_North,Mountain,CO,western,USA,mountain,Mountain,Public_Service_Co_of_Colorado,p34
-p35,SPP,SPP,SPP_North,West_North_Central,MT,eastern,USA,mountain,Mountain,SPP,p35
-p36,SPP,SPP,SPP_North,West_North_Central,ND,eastern,USA,northern-plains,Plains,SPP,p36
-p37,MISO,MISO,MISO_North,West_North_Central,ND,eastern,USA,northern-plains,Plains,MISO,p37
-p38,SPP,SPP,SPP_North,West_North_Central,SD,eastern,USA,northern-plains,Plains,SPP,p38
-p39,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,p39
-p40,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,p40
-p41,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,p41
-p42,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p42
-p43,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p43
-p44,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p44
-p45,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p45
-p46,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p46
-p47,SPP,SPP,SPP_South,West_South_Central,NM,eastern,USA,mountain,Southwest,SPP,p47
-p48,SPP,SPP,SPP_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,SPP,p48
-p49,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,p49
-p50,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,p50
-p51,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,p51
-p52,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,p52
-p53,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,p53
-p54,SPP,SPP,SPP_South,West_North_Central,MO,eastern,USA,corn-belt,Midwest,SPP,p54
-p55,SPP,SPP,SPP_South,West_North_Central,MO,eastern,USA,corn-belt,Midwest,SPP,p55
-p56,SPP,SPP,SPP_South,West_South_Central,AR,eastern,USA,delta-states,Delta,SPP,p56
-p57,SPP,SPP,SPP_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,SPP,p57
-p58,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,p58
-p59,WECC_SW,WestConnect,WestConnect_South,Mountain,TX,western,USA,southern-plains,Texas,El_Paso_Electric,p59
-p60,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p60
-p61,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p61
-p62,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p62
-p63,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p63
-p64,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p64
-p65,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p65
-p66,MISO,MISO,MISO_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,MISO,p66
-p67,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p67
-p68,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,p68
-p69,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p69
-p70,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p70
-p71,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p71
-p72,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p72
-p73,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p73
-p74,MISO,MISO,MISO_North,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,p74
-p75,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p75
-p76,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p76
-p77,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p77
-p78,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p78
-p79,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p79
-p80,PJM,PJM,PJM_West,East_North_Central,IL,eastern,USA,corn-belt,Midwest,PJM,p80
-p81,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p81
-p82,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p82
-p83,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p83
-p84,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p84
-p85,MISO,MISO,MISO_South,West_South_Central,AR,eastern,USA,delta-states,Delta,MISO,p85
-p86,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,p86
-p87,MISO,MISO,MISO_South,East_South_Central,MS,eastern,USA,delta-states,Delta,MISO,p87
-p88,SERC_C,SERTP,SERTP,East_South_Central,MS,eastern,USA,delta-states,Delta,Tennessee_Valley_Authority,p88
-p89,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,Southern_Co_Services_Inc,p89
-p90,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,PowerSouth_Energy_Coop,p90
-p91,SERC_SE,SERTP,SERTP,South_Atlantic,FL,eastern,USA,southeast,Florida,Southern_Co_Services_Inc,p91
-p92,SERC_C,SERTP,SERTP,East_South_Central,TN,eastern,USA,appalachia,Southeast,Tennessee_Valley_Authority,p92
-p93,SERC_C,SERTP,SERTP,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,Tennessee_Valley_Authority,p93
-p94,SERC_SE,SERTP,SERTP,South_Atlantic,GA,eastern,USA,southeast,Southeast,Southern_Co_Services_Inc,p94
-p95,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,Duke_Energy_Carolinas_LLC,p95
-p96,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,South_Carolina_Electric_Gas_Co,p96
-p97,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Carolinas_LLC,p97
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-p118,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p118
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-p123,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,p123
-p124,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p124
-p125,PJM,PJM,PJM_East,South_Atlantic,DE,eastern,USA,northeast,MidAtlantic,PJM,p125
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-p127,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,p127
-p128,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,p128
-p129,NPCC_NE,ISONE,ISONE,New_England,VT,eastern,USA,northeast,NewEngland,ISONE,p129
-p130,NPCC_NE,ISONE,ISONE,New_England,NH,eastern,USA,northeast,NewEngland,ISONE,p130
-p131,NPCC_NE,ISONE,ISONE,New_England,MA,eastern,USA,northeast,NewEngland,ISONE,p131
-p132,NPCC_NE,ISONE,ISONE,New_England,CT,eastern,USA,northeast,NewEngland,ISONE,p132
-p133,NPCC_NE,ISONE,ISONE,New_England,RI,eastern,USA,northeast,NewEngland,ISONE,p133
-p134,NPCC_NE,ISONE,ISONE,New_England,ME,eastern,USA,northeast,NewEngland,ISONE,p134
diff --git a/inputs/zones/z134/hierarchy.csv b/inputs/zones/z134/hierarchy.csv
index 3cc8ecd3..f68801de 100644
--- a/inputs/zones/z134/hierarchy.csv
+++ b/inputs/zones/z134/hierarchy.csv
@@ -1,135 +1,135 @@
-r,nercr,transreg,transgrp,st,interconnect,hurdlereg,aggreg
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-p6,WECC_NW,NorthernGrid,NorthernGrid_West,OR,western,PacifiCorp_West,p6
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-p11,WECC_CA,CAISO,CAISO,CA,western,CAISO,p11
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-p13,WECC_NW,NorthernGrid,NorthernGrid_South,NV,western,Nevada_Power_Co,p13
-p14,WECC_NW,NorthernGrid,NorthernGrid_East,ID,western,Avista_Corp,p14
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-p16,WECC_NW,NorthernGrid,NorthernGrid_East,ID,western,Idaho_Power_Co,p16
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-p18,WECC_NW,NorthernGrid,NorthernGrid_East,MT,western,Northwestern_Energy,p18
-p19,WECC_NW,NorthernGrid,NorthernGrid_East,MT,western,WAPA_Upper_Great_Plains_West,p19
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-p26,WECC_NW,NorthernGrid,NorthernGrid_South,UT,western,PacifiCorp_East,p26
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+r,nercr,transreg,transgrp,st,interconnect,hurdlereg
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diff --git a/inputs/zones/z134/hierarchy_from134.csv b/inputs/zones/z134/hierarchy_from134.csv
deleted file mode 100644
index c1b5a1a7..00000000
--- a/inputs/zones/z134/hierarchy_from134.csv
+++ /dev/null
@@ -1,135 +0,0 @@
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diff --git a/inputs/zones/z3109/hierarchy_from134.csv b/inputs/zones/z3109/hierarchy_from134.csv
deleted file mode 100644
index c1b5a1a7..00000000
--- a/inputs/zones/z3109/hierarchy_from134.csv
+++ /dev/null
@@ -1,135 +0,0 @@
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-p17,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p17
-p18,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,p18
-p19,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,WAPA_Upper_Great_Plains_West,p19
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-p21,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,p21
-p22,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,p22
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-p26,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,p26
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-p51,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,p51
-p52,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,p52
-p53,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,p53
-p54,SPP,SPP,SPP_South,West_North_Central,MO,eastern,USA,corn-belt,Midwest,SPP,p54
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-p65,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p65
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-p67,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,p67
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-p69,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p69
-p70,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,p70
-p71,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p71
-p72,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p72
-p73,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p73
-p74,MISO,MISO,MISO_North,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,p74
-p75,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p75
-p76,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p76
-p77,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p77
-p78,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p78
-p79,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,p79
-p80,PJM,PJM,PJM_West,East_North_Central,IL,eastern,USA,corn-belt,Midwest,PJM,p80
-p81,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p81
-p82,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p82
-p83,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,p83
-p84,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,p84
-p85,MISO,MISO,MISO_South,West_South_Central,AR,eastern,USA,delta-states,Delta,MISO,p85
-p86,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,p86
-p87,MISO,MISO,MISO_South,East_South_Central,MS,eastern,USA,delta-states,Delta,MISO,p87
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-p89,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,Southern_Co_Services_Inc,p89
-p90,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,PowerSouth_Energy_Coop,p90
-p91,SERC_SE,SERTP,SERTP,South_Atlantic,FL,eastern,USA,southeast,Florida,Southern_Co_Services_Inc,p91
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-p95,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,Duke_Energy_Carolinas_LLC,p95
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-p104,PJM,PJM,PJM_West,East_North_Central,MI,eastern,USA,lake-states,Midwest,PJM,p104
-p105,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,p105
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-p107,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,p107
-p108,MISO,MISO,MISO_Central,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,MISO,p108
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-p110,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,p110
-p111,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p111
-p112,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p112
-p113,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p113
-p114,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,p114
-p115,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,p115
-p116,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,p116
-p117,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,p117
-p118,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p118
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-p120,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,p120
-p121,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,p121
-p122,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,z122
-p123,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,p123
-p124,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,p124
-p125,PJM,PJM,PJM_East,South_Atlantic,DE,eastern,USA,northeast,MidAtlantic,PJM,p125
-p126,PJM,PJM,PJM_East,Mid_Atlantic,NJ,eastern,USA,northeast,MidAtlantic,PJM,p126
-p127,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,p127
-p128,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,p128
-p129,NPCC_NE,ISONE,ISONE,New_England,VT,eastern,USA,northeast,NewEngland,ISONE,p129
-p130,NPCC_NE,ISONE,ISONE,New_England,NH,eastern,USA,northeast,NewEngland,ISONE,p130
-p131,NPCC_NE,ISONE,ISONE,New_England,MA,eastern,USA,northeast,NewEngland,ISONE,p131
-p132,NPCC_NE,ISONE,ISONE,New_England,CT,eastern,USA,northeast,NewEngland,ISONE,p132
-p133,NPCC_NE,ISONE,ISONE,New_England,RI,eastern,USA,northeast,NewEngland,ISONE,p133
-p134,NPCC_NE,ISONE,ISONE,New_England,ME,eastern,USA,northeast,NewEngland,ISONE,p134
diff --git a/inputs/zones/z48/hierarchy_from134.csv b/inputs/zones/z48/hierarchy_from134.csv
deleted file mode 100644
index c0275442..00000000
--- a/inputs/zones/z48/hierarchy_from134.csv
+++ /dev/null
@@ -1,135 +0,0 @@
-ba,nercr,transreg,transgrp,cendiv,st,interconnect,country,usda_region,h2ptcreg,hurdlereg,aggreg
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-p2,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,WA
-p3,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,WA
-p4,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,WA
-p5,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,OR
-p6,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,OR
-p7,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,OR
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-p11,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,CA
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-p23,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,WY
-p24,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,WY
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-p26,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,UT
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-p48,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX
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-p50,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,OK
-p51,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,OK
-p52,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,KS
-p53,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,KS
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-p56,MISO,MISO,MISO_South,West_South_Central,AR,eastern,USA,delta-states,Delta,MISO,AR
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-p63,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX
-p64,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX
-p65,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX
-p66,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX
-p67,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX
-p68,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,MN
-p69,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,IA
-p70,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,IA
-p71,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,MO
-p72,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,MO
-p73,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,MO
-p74,MISO,MISO,MISO_Central,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,MI
-p75,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p76,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p77,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p78,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p79,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p80,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,IL
-p81,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,IL
-p82,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,IL
-p83,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,IL
-p84,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,MO
-p85,MISO,MISO,MISO_South,West_South_Central,AR,eastern,USA,delta-states,Delta,MISO,AR
-p86,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,LA
-p87,MISO,MISO,MISO_South,East_South_Central,MS,eastern,USA,delta-states,Delta,MISO,MS
-p88,MISO,MISO,MISO_South,East_South_Central,MS,eastern,USA,delta-states,Delta,MISO,MS
-p89,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,PowerSouth_Energy_Coop,AL
-p90,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,PowerSouth_Energy_Coop,AL
-p91,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Seminole_Electric_Coop_Inc,FL
-p92,SERC_C,SERTP,SERTP,East_South_Central,TN,eastern,USA,appalachia,Southeast,Tennessee_Valley_Authority,TN
-p93,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,KY
-p94,SERC_SE,SERTP,SERTP,South_Atlantic,GA,eastern,USA,southeast,Southeast,Southern_Co_Services_Inc,GA
-p95,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,Duke_Energy_Carolinas_LLC,SC
-p96,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,Duke_Energy_Carolinas_LLC,SC
-p97,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Carolinas_LLC,NC
-p98,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Carolinas_LLC,NC
-p99,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p100,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p101,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Seminole_Electric_Coop_Inc,FL
-p102,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Seminole_Electric_Coop_Inc,FL
-p103,MISO,MISO,MISO_Central,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,MI
-p104,MISO,MISO,MISO_Central,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,MI
-p105,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,IN
-p106,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,IN
-p107,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,IN
-p108,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,KY
-p109,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,KY
-p110,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,KY
-p111,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,OH
-p112,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,OH
-p113,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,OH
-p114,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,OH
-p115,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p116,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,WV
-p117,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,WV
-p118,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p119,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p120,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p121,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,MD
-p122,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p123,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,MD
-p124,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p125,PJM,PJM,PJM_East,South_Atlantic,DE,eastern,USA,northeast,MidAtlantic,PJM,DE
-p126,PJM,PJM,PJM_East,Mid_Atlantic,NJ,eastern,USA,northeast,MidAtlantic,PJM,NJ
-p127,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,NY
-p128,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,NY
-p129,NPCC_NE,ISONE,ISONE,New_England,VT,eastern,USA,northeast,NewEngland,ISONE,VT
-p130,NPCC_NE,ISONE,ISONE,New_England,NH,eastern,USA,northeast,NewEngland,ISONE,NH
-p131,NPCC_NE,ISONE,ISONE,New_England,MA,eastern,USA,northeast,NewEngland,ISONE,MA
-p132,NPCC_NE,ISONE,ISONE,New_England,CT,eastern,USA,northeast,NewEngland,ISONE,CT
-p133,NPCC_NE,ISONE,ISONE,New_England,RI,eastern,USA,northeast,NewEngland,ISONE,RI
-p134,NPCC_NE,ISONE,ISONE,New_England,ME,eastern,USA,northeast,NewEngland,ISONE,ME
diff --git a/inputs/zones/z54/hierarchy_from134.csv b/inputs/zones/z54/hierarchy_from134.csv
deleted file mode 100644
index 59b418b3..00000000
--- a/inputs/zones/z54/hierarchy_from134.csv
+++ /dev/null
@@ -1,135 +0,0 @@
-ba,nercr,transreg,transgrp,cendiv,st,interconnect,country,usda_region,h2ptcreg,hurdlereg,aggreg
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-p2,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,WA
-p3,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,WA
-p4,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,WA
-p5,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,OR
-p6,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,OR
-p7,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,OR
-p8,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,CA_N
-p9,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,CA_N
-p10,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,CA_S
-p11,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,CA_S
-p12,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,NV,western,USA,mountain,Mountain,Nevada_Power_Co,NV
-p13,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,NV,western,USA,mountain,Mountain,Nevada_Power_Co,NV
-p14,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,ID
-p15,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,ID
-p16,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,ID
-p17,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,MT
-p18,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,MT
-p19,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,MT
-p20,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,MT
-p21,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,WY
-p22,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,WY
-p23,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,WY
-p24,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,WY
-p25,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,UT
-p26,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,UT
-p27,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,AZ
-p28,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,AZ
-p29,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,AZ
-p30,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,AZ
-p31,WECC_SW,WestConnect,WestConnect_South,Mountain,NM,western,USA,mountain,Southwest,Public_Service_Co_of_New_Mexico,NM
-p32,SPP,SPP,SPP_North,West_North_Central,SD,eastern,USA,northern-plains,Plains,SPP,SD
-p33,WECC_NW,WestConnect,WestConnect_North,Mountain,CO,western,USA,mountain,Mountain,Public_Service_Co_of_Colorado,CO
-p34,WECC_NW,WestConnect,WestConnect_North,Mountain,CO,western,USA,mountain,Mountain,Public_Service_Co_of_Colorado,CO
-p35,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,MT
-p36,SPP,SPP,SPP_North,West_North_Central,ND,eastern,USA,northern-plains,Plains,SPP,ND
-p37,SPP,SPP,SPP_North,West_North_Central,ND,eastern,USA,northern-plains,Plains,SPP,ND
-p38,SPP,SPP,SPP_North,West_North_Central,SD,eastern,USA,northern-plains,Plains,SPP,SD
-p39,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,NE
-p40,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,NE
-p41,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,NE
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-p43,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,MN
-p44,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,MN
-p45,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,IA
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-p47,WECC_SW,WestConnect,WestConnect_South,Mountain,NM,western,USA,mountain,Southwest,Public_Service_Co_of_New_Mexico,NM
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-p50,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,OK
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-p52,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,KS
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-p85,MISO,MISO,MISO_South,West_South_Central,AR,eastern,USA,delta-states,Delta,MISO,AR
-p86,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,LA
-p87,MISO,MISO,MISO_South,East_South_Central,MS,eastern,USA,delta-states,Delta,MISO,MS
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-p90,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,PowerSouth_Energy_Coop,AL
-p91,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Seminole_Electric_Coop_Inc,FL
-p92,SERC_C,SERTP,SERTP,East_South_Central,TN,eastern,USA,appalachia,Southeast,Tennessee_Valley_Authority,TN
-p93,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,KY
-p94,SERC_SE,SERTP,SERTP,South_Atlantic,GA,eastern,USA,southeast,Southeast,Southern_Co_Services_Inc,GA
-p95,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,Duke_Energy_Carolinas_LLC,SC
-p96,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,Duke_Energy_Carolinas_LLC,SC
-p97,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Carolinas_LLC,NC
-p98,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Carolinas_LLC,NC
-p99,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p100,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p101,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Seminole_Electric_Coop_Inc,FL
-p102,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Seminole_Electric_Coop_Inc,FL
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-p104,MISO,MISO,MISO_Central,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,MI
-p105,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,IN
-p106,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,IN
-p107,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,IN
-p108,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,KY
-p109,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,KY
-p110,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,KY
-p111,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,OH
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-p114,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,OH
-p115,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p116,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,WV
-p117,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,WV
-p118,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p119,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p120,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p121,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,MD
-p122,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p123,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,MD
-p124,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p125,PJM,PJM,PJM_East,South_Atlantic,DE,eastern,USA,northeast,MidAtlantic,PJM,DE
-p126,PJM,PJM,PJM_East,Mid_Atlantic,NJ,eastern,USA,northeast,MidAtlantic,PJM,NJ
-p127,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,NY_UP
-p128,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,NY_NYCLI
-p129,NPCC_NE,ISONE,ISONE,New_England,VT,eastern,USA,northeast,NewEngland,ISONE,VT
-p130,NPCC_NE,ISONE,ISONE,New_England,NH,eastern,USA,northeast,NewEngland,ISONE,NH
-p131,NPCC_NE,ISONE,ISONE,New_England,MA,eastern,USA,northeast,NewEngland,ISONE,MA
-p132,NPCC_NE,ISONE,ISONE,New_England,CT,eastern,USA,northeast,NewEngland,ISONE,CT
-p133,NPCC_NE,ISONE,ISONE,New_England,RI,eastern,USA,northeast,NewEngland,ISONE,RI
-p134,NPCC_NE,ISONE,ISONE,New_England,ME,eastern,USA,northeast,NewEngland,ISONE,ME
diff --git a/inputs/zones/z69/hierarchy_from134.csv b/inputs/zones/z69/hierarchy_from134.csv
deleted file mode 100644
index 8a2d12aa..00000000
--- a/inputs/zones/z69/hierarchy_from134.csv
+++ /dev/null
@@ -1,135 +0,0 @@
-ba,nercr,transreg,transgrp,cendiv,st,interconnect,country,usda_region,h2ptcreg,hurdlereg,aggreg
-p1,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,WA
-p2,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,WA
-p3,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,WA
-p4,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,WA,western,USA,pacific,Northwest,Bonneville_Power_Administration,WA
-p5,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,OR
-p6,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,OR
-p7,WECC_NW,NorthernGrid,NorthernGrid_West,Pacific,OR,western,USA,pacific,Northwest,Bonneville_Power_Administration,OR
-p8,WECC_NW,NorthernGrid,NorthernGrid_South,Pacific,CA,western,USA,pacific,California,PacifiCorp_West,CA_NorthernGrid
-p9,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,CA_N_CAISO
-p10,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,CA_S_CAISO
-p11,WECC_CA,CAISO,CAISO,Pacific,CA,western,USA,pacific,California,CAISO,CA_S_CAISO
-p12,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,NV,western,USA,mountain,Mountain,Nevada_Power_Co,NV
-p13,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,NV,western,USA,mountain,Mountain,Nevada_Power_Co,NV
-p14,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,ID
-p15,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,ID
-p16,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,ID,western,USA,mountain,Northwest,Idaho_Power_Co,ID
-p17,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,MT_NorthernGrid
-p18,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,MT_NorthernGrid
-p19,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,MT_NorthernGrid
-p20,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,MT,western,USA,mountain,Mountain,Northwestern_Energy,MT_NorthernGrid
-p21,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,WY_NorthernGrid
-p22,WECC_NW,NorthernGrid,NorthernGrid_East,Mountain,WY,western,USA,mountain,Mountain,PacifiCorp_East,WY_NorthernGrid
-p23,WECC_NW,WestConnect,WestConnect_North,Mountain,WY,western,USA,mountain,Mountain,WAPA_Rocky_Mountain_Region,WY_WestConnect
-p24,WECC_NW,WestConnect,WestConnect_North,Mountain,WY,western,USA,mountain,Mountain,WAPA_Rocky_Mountain_Region,WY_WestConnect
-p25,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,UT
-p26,WECC_NW,NorthernGrid,NorthernGrid_South,Mountain,UT,western,USA,mountain,Mountain,PacifiCorp_East,UT
-p27,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,AZ
-p28,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,AZ
-p29,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,AZ
-p30,WECC_SW,WestConnect,WestConnect_South,Mountain,AZ,western,USA,mountain,Southwest,Arizona_Public_Service_Co,AZ
-p31,WECC_SW,WestConnect,WestConnect_South,Mountain,NM,western,USA,mountain,Southwest,Public_Service_Co_of_New_Mexico,NM_WestConnect
-p32,WECC_NW,WestConnect,WestConnect_North,Mountain,SD,western,USA,northern-plains,Plains,WAPA_Rocky_Mountain_Region,SD_WestConnect
-p33,WECC_NW,WestConnect,WestConnect_North,Mountain,CO,western,USA,mountain,Mountain,Public_Service_Co_of_Colorado,CO
-p34,WECC_NW,WestConnect,WestConnect_North,Mountain,CO,western,USA,mountain,Mountain,Public_Service_Co_of_Colorado,CO
-p35,SPP,SPP,SPP_North,West_North_Central,MT,eastern,USA,mountain,Mountain,SPP,MT_SPP
-p36,SPP,SPP,SPP_North,West_North_Central,ND,eastern,USA,northern-plains,Plains,SPP,ND_SPP
-p37,MISO,MISO,MISO_North,West_North_Central,ND,eastern,USA,northern-plains,Plains,MISO,ND_MISO
-p38,SPP,SPP,SPP_North,West_North_Central,SD,eastern,USA,northern-plains,Plains,SPP,SD_SPP
-p39,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,NE
-p40,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,NE
-p41,SPP,SPP,SPP_North,West_North_Central,NE,eastern,USA,northern-plains,Plains,SPP,NE
-p42,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,MN
-p43,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,MN
-p44,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,MN
-p45,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,IA
-p46,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p47,SPP,SPP,SPP_South,West_South_Central,NM,eastern,USA,mountain,Southwest,SPP,NM_SPP
-p48,SPP,SPP,SPP_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,SPP,TX_SPP_N
-p49,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,OK
-p50,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,OK
-p51,SPP,SPP,SPP_South,West_South_Central,OK,eastern,USA,southern-plains,Plains,SPP,OK
-p52,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,KS
-p53,SPP,SPP,SPP_South,West_North_Central,KS,eastern,USA,northern-plains,Plains,SPP,KS
-p54,SPP,SPP,SPP_South,West_North_Central,MO,eastern,USA,corn-belt,Midwest,SPP,MO_SPP
-p55,SPP,SPP,SPP_South,West_North_Central,MO,eastern,USA,corn-belt,Midwest,SPP,MO_SPP
-p56,SPP,SPP,SPP_South,West_South_Central,AR,eastern,USA,delta-states,Delta,SPP,AR_SPP
-p57,SPP,SPP,SPP_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,SPP,TX_SPP_E
-p58,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,LA
-p59,WECC_SW,WestConnect,WestConnect_South,Mountain,TX,western,USA,southern-plains,Texas,El_Paso_Electric,TX_WestConnect
-p60,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX_W_ERCOT
-p61,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX_W_ERCOT
-p62,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX_W_ERCOT
-p63,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX_E_ERCOT
-p64,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX_E_ERCOT
-p65,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX_E_ERCOT
-p66,MISO,MISO,MISO_South,West_South_Central,TX,eastern,USA,southern-plains,Texas,MISO,TX_MISO
-p67,ERCOT,ERCOT,ERCOT,West_South_Central,TX,texas,USA,southern-plains,Texas,ERCOT,TX_E_ERCOT
-p68,MISO,MISO,MISO_North,West_North_Central,MN,eastern,USA,lake-states,Midwest,MISO,MN
-p69,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,IA
-p70,MISO,MISO,MISO_North,West_North_Central,IA,eastern,USA,corn-belt,Midwest,MISO,IA
-p71,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,MO_MISO
-p72,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,MO_MISO
-p73,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,MO_MISO
-p74,MISO,MISO,MISO_Central,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,MI_MISO
-p75,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p76,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p77,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p78,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p79,MISO,MISO,MISO_North,East_North_Central,WI,eastern,USA,lake-states,Midwest,MISO,WI
-p80,PJM,PJM,PJM_West,East_North_Central,IL,eastern,USA,corn-belt,Midwest,PJM,IL_PJM
-p81,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,IL_MISO
-p82,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,IL_MISO
-p83,MISO,MISO,MISO_Central,East_North_Central,IL,eastern,USA,corn-belt,Midwest,MISO,IL_MISO
-p84,MISO,MISO,MISO_Central,West_North_Central,MO,eastern,USA,corn-belt,Midwest,MISO,MO_MISO
-p85,MISO,MISO,MISO_South,West_South_Central,AR,eastern,USA,delta-states,Delta,MISO,AR_MISO
-p86,MISO,MISO,MISO_South,West_South_Central,LA,eastern,USA,delta-states,Delta,MISO,LA
-p87,MISO,MISO,MISO_South,East_South_Central,MS,eastern,USA,delta-states,Delta,MISO,MS_MISO
-p88,SERC_C,SERTP,SERTP,East_South_Central,MS,eastern,USA,delta-states,Delta,Tennessee_Valley_Authority,MS_SERTP
-p89,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,PowerSouth_Energy_Coop,AL
-p90,SERC_SE,SERTP,SERTP,East_South_Central,AL,eastern,USA,southeast,Southeast,PowerSouth_Energy_Coop,AL
-p91,SERC_SE,SERTP,SERTP,South_Atlantic,FL,eastern,USA,southeast,Florida,Southern_Co_Services_Inc,FL_SERTP
-p92,SERC_C,SERTP,SERTP,East_South_Central,TN,eastern,USA,appalachia,Southeast,Tennessee_Valley_Authority,TN
-p93,SERC_C,SERTP,SERTP,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,Tennessee_Valley_Authority,KY_SERTP
-p94,SERC_SE,SERTP,SERTP,South_Atlantic,GA,eastern,USA,southeast,Southeast,Southern_Co_Services_Inc,GA
-p95,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,South_Carolina_Electric_Gas_Co,SC
-p96,SERC_E,SERTP,SERTP,South_Atlantic,SC,eastern,USA,southeast,Southeast,South_Carolina_Electric_Gas_Co,SC
-p97,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Carolinas_LLC,NC
-p98,SERC_E,SERTP,SERTP,South_Atlantic,NC,eastern,USA,appalachia,Southeast,Duke_Energy_Carolinas_LLC,NC
-p99,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p100,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p101,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Seminole_Electric_Coop_Inc,FL_FRCC
-p102,SERC_F,FRCC,FRCC,South_Atlantic,FL,eastern,USA,southeast,Florida,Seminole_Electric_Coop_Inc,FL_FRCC
-p103,MISO,MISO,MISO_Central,East_North_Central,MI,eastern,USA,lake-states,Midwest,MISO,MI_MISO
-p104,PJM,PJM,PJM_West,East_North_Central,MI,eastern,USA,lake-states,Midwest,PJM,MI_PJM
-p105,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,IN
-p106,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,IN
-p107,MISO,MISO,MISO_Central,East_North_Central,IN,eastern,USA,corn-belt,Midwest,MISO,IN
-p108,MISO,MISO,MISO_Central,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,MISO,KY_MISO
-p109,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,KY_PJM
-p110,PJM,PJM,PJM_East,East_South_Central,KY,eastern,USA,appalachia,MidAtlantic,PJM,KY_PJM
-p111,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,OH
-p112,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,OH
-p113,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,OH
-p114,PJM,PJM,PJM_East,East_North_Central,OH,eastern,USA,corn-belt,MidAtlantic,PJM,OH
-p115,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p116,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,WV
-p117,PJM,PJM,PJM_East,South_Atlantic,WV,eastern,USA,appalachia,MidAtlantic,PJM,WV
-p118,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p119,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p120,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p121,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,MD
-p122,PJM,PJM,PJM_East,Mid_Atlantic,PA,eastern,USA,northeast,MidAtlantic,PJM,PA
-p123,PJM,PJM,PJM_East,South_Atlantic,MD,eastern,USA,northeast,MidAtlantic,PJM,MD
-p124,PJM,PJM,PJM_East,South_Atlantic,VA,eastern,USA,appalachia,MidAtlantic,PJM,VA
-p125,PJM,PJM,PJM_East,South_Atlantic,DE,eastern,USA,northeast,MidAtlantic,PJM,DE
-p126,PJM,PJM,PJM_East,Mid_Atlantic,NJ,eastern,USA,northeast,MidAtlantic,PJM,NJ
-p127,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,NY_UP
-p128,NPCC_NY,NYISO,NYISO,Mid_Atlantic,NY,eastern,USA,northeast,NewYork,NYISO,NY_NYCLI
-p129,NPCC_NE,ISONE,ISONE,New_England,VT,eastern,USA,northeast,NewEngland,ISONE,VT
-p130,NPCC_NE,ISONE,ISONE,New_England,NH,eastern,USA,northeast,NewEngland,ISONE,NH
-p131,NPCC_NE,ISONE,ISONE,New_England,MA,eastern,USA,northeast,NewEngland,ISONE,MA
-p132,NPCC_NE,ISONE,ISONE,New_England,CT,eastern,USA,northeast,NewEngland,ISONE,CT
-p133,NPCC_NE,ISONE,ISONE,New_England,RI,eastern,USA,northeast,NewEngland,ISONE,RI
-p134,NPCC_NE,ISONE,ISONE,New_England,ME,eastern,USA,northeast,NewEngland,ISONE,ME
diff --git a/inputs/zones/z90/hierarchy.csv b/inputs/zones/z90/hierarchy.csv
index 6930a59f..75d65f7a 100644
--- a/inputs/zones/z90/hierarchy.csv
+++ b/inputs/zones/z90/hierarchy.csv
@@ -1,91 +1,91 @@
-r,st,transreg,transgrp,nercr,interconnect
-WA_W,WA,NorthernGrid,NorthernGrid_West,WECC_NW,western
-WA_E,WA,NorthernGrid,NorthernGrid_West,WECC_NW,western
-OR_W,OR,NorthernGrid,NorthernGrid_West,WECC_NW,western
-OR_E,OR,NorthernGrid,NorthernGrid_West,WECC_NW,western
-CA_N,CA,CAISO,CAISO,WECC_CA,western
-CA_S,CA,CAISO,CAISO,WECC_CA,western
-CA_LA,CA,CAISO,CAISO,WECC_CA,western
-CA_SE,CA,CAISO,CAISO,WECC_CA,western
-ID_N,ID,NorthernGrid,NorthernGrid_East,WECC_NW,western
-ID_S,ID,NorthernGrid,NorthernGrid_East,WECC_NW,western
-MT_W,MT,NorthernGrid,NorthernGrid_East,WECC_NW,western
-MT_C,MT,NorthernGrid,NorthernGrid_East,WECC_NW,western
-MT_E,MT,SPP,SPP_North,SPP,eastern
-NV_N,NV,NorthernGrid,NorthernGrid_South,WECC_NW,western
-NV_LV,NV,NorthernGrid,NorthernGrid_South,WECC_NW,western
-UT,UT,NorthernGrid,NorthernGrid_South,WECC_NW,western
-WY_W,WY,NorthernGrid,NorthernGrid_East,WECC_NW,western
-WY_E,WY,WestConnect,WestConnect_North,WECC_NW,western
-CO_W,CO,WestConnect,WestConnect_North,WECC_NW,western
-CO_E,CO,WestConnect,WestConnect_North,WECC_NW,western
-AZ_N,AZ,WestConnect,WestConnect_South,WECC_SW,western
-AZ_S,AZ,WestConnect,WestConnect_South,WECC_SW,western
-NM_W,NM,WestConnect,WestConnect_South,WECC_SW,western
-NM_E,NM,SPP,SPP_South,SPP,eastern
-TX_EP,TX,WestConnect,WestConnect_South,WestConnect,western
-TX_N,TX,ERCOT,ERCOT,ERCOT,texas
-TX_W,TX,ERCOT,ERCOT,ERCOT,texas
-TX_S,TX,ERCOT,ERCOT,ERCOT,texas
-TX_PAN,TX,SPP,SPP_South,SPP,eastern
-TX_SPP,TX,SPP,SPP_South,SPP,eastern
-TX_HOU,TX,ERCOT,ERCOT,ERCOT,texas
-TX_MISO,TX,MISO,MISO_South,MISO,eastern
-ND_SPP,ND,SPP,SPP_North,SPP,eastern
-ND_MISO,ND,MISO,MISO_North,MISO,eastern
-SD,SD,SPP,SPP_North,SPP,eastern
-NE,NE,SPP,SPP_North,SPP,eastern
-KS,KS,SPP,SPP_South,SPP,eastern
-OK,OK,SPP,SPP_South,SPP,eastern
-MN_N,MN,MISO,MISO_North,MISO,eastern
-MN_S,MN,MISO,MISO_North,MISO,eastern
-WI_W,WI,MISO,MISO_North,MISO,eastern
-WI_E,WI,MISO,MISO_North,MISO,eastern
-IA,IA,MISO,MISO_Central,MISO,eastern
-MO_SPP,MO,SPP,SPP_South,SPP,eastern
-MO_MISO,MO,MISO,MISO_Central,MISO,eastern
-MO_SE,MO,SERTP,SERTP,SERC_C,eastern
-AR_SPP,AR,SPP,SPP_South,SPP,eastern
-AR_MISO,AR,MISO,MISO_South,MISO,eastern
-LA,LA,MISO,MISO_South,MISO,eastern
-MI_UP,MI,MISO,MISO_North,MISO,eastern
-MI_LP,MI,MISO,MISO_North,MISO,eastern
-MI_PJM,MI,PJM,PJM_West,PJM,eastern
-IL_PJM,IL,PJM,PJM_West,PJM,eastern
-IL_MISO,IL,MISO,MISO_Central,MISO,eastern
-IN_PJM,IN,PJM,PJM_West,PJM,eastern
-IN_MISO,IN,MISO,MISO_Central,MISO,eastern
-KY_PJM,KY,PJM,PJM_East,PJM,eastern
-KY_MISO,KY,MISO,MISO_Central,MISO,eastern
-MS_MISO,MS,MISO,MISO_South,MISO,eastern
-MS_SE,MS,SERTP,SERTP,SERC_C,eastern
-TN,TN,SERTP,SERTP,SERC_C,eastern
-AL,AL,SERTP,SERTP,SERC_SE,eastern
-GA_N,GA,SERTP,SERTP,SERC_SE,eastern
-GA_S,GA,SERTP,SERTP,SERC_SE,eastern
-SC,SC,SERTP,SERTP,SERC_E,eastern
-NC_SE,NC,SERTP,SERTP,SERC_E,eastern
-NC_PJM,NC,PJM,PJM_East,SERC_E,eastern
-FL_N,FL,FRCC,FRCC,SERC_F,eastern
-FL_S,FL,FRCC,FRCC,SERC_F,eastern
-FL_SE,FL,FRCC,FRCC,SERC_F,eastern
-OH_N,OH,PJM,PJM_East,PJM,eastern
-OH_S,OH,PJM,PJM_East,PJM,eastern
-WV,WV,PJM,PJM_East,PJM,eastern
-VA_W,VA,PJM,PJM_East,PJM,eastern
-VA_E,VA,PJM,PJM_East,PJM,eastern
-PA_W,PA,PJM,PJM_East,PJM,eastern
-PA_E,PA,PJM,PJM_East,PJM,eastern
-MD,MD,PJM,PJM_East,PJM,eastern
-DE,DE,PJM,PJM_East,PJM,eastern
-NJ,NJ,PJM,PJM_East,PJM,eastern
-NY_W,NY,NYISO,NYISO,NPCC_NY,eastern
-NY_E,NY,NYISO,NYISO,NPCC_NY,eastern
-NY_NYC,NY,NYISO,NYISO,NPCC_NY,eastern
-NY_LI,NY,NYISO,NYISO,NPCC_NY,eastern
-VT,VT,ISONE,ISONE,NPCC_NE,eastern
-NH,NH,ISONE,ISONE,NPCC_NE,eastern
-MA,MA,ISONE,ISONE,NPCC_NE,eastern
-CT,CT,ISONE,ISONE,NPCC_NE,eastern
-RI,RI,ISONE,ISONE,NPCC_NE,eastern
-ME,ME,ISONE,ISONE,NPCC_NE,eastern
+r,st,transreg,transgrp,nercr,interconnect,hurdlereg
+WA_W,WA,NorthernGrid,NorthernGrid_West,WECC_NW,western,Bonneville_Power_Administration
+WA_E,WA,NorthernGrid,NorthernGrid_West,WECC_NW,western,Avista_Corp
+OR_W,OR,NorthernGrid,NorthernGrid_West,WECC_NW,western,Bonneville_Power_Administration
+OR_E,OR,NorthernGrid,NorthernGrid_West,WECC_NW,western,Bonneville_Power_Administration
+CA_N,CA,CAISO,CAISO,WECC_CA,western,CAISO
+CA_S,CA,CAISO,CAISO,WECC_CA,western,CAISO
+CA_LA,CA,CAISO,CAISO,WECC_CA,western,CAISO
+CA_SE,CA,CAISO,CAISO,WECC_CA,western,CAISO
+ID_N,ID,NorthernGrid,NorthernGrid_East,WECC_NW,western,Bonneville_Power_Administration
+ID_S,ID,NorthernGrid,NorthernGrid_East,WECC_NW,western,Idaho_Power_Co
+MT_W,MT,NorthernGrid,NorthernGrid_East,WECC_NW,western,Northwestern_Energy
+MT_C,MT,NorthernGrid,NorthernGrid_East,WECC_NW,western,Northwestern_Energy
+MT_E,MT,SPP,SPP_North,SPP,eastern,MISO
+NV_N,NV,NorthernGrid,NorthernGrid_South,WECC_NW,western,Nevada_Power_Co
+NV_LV,NV,NorthernGrid,NorthernGrid_South,WECC_NW,western,Nevada_Power_Co
+UT,UT,NorthernGrid,NorthernGrid_South,WECC_NW,western,PacifiCorp_East
+WY_W,WY,NorthernGrid,NorthernGrid_East,WECC_NW,western,PacifiCorp_East
+WY_E,WY,WestConnect,WestConnect_North,WECC_NW,western,WAPA_Rocky_Mountain_Region
+CO_W,CO,WestConnect,WestConnect_North,WECC_NW,western,WAPA_Rocky_Mountain_Region
+CO_E,CO,WestConnect,WestConnect_North,WECC_NW,western,WAPA_Rocky_Mountain_Region
+AZ_N,AZ,WestConnect,WestConnect_South,WECC_SW,western,Arizona_Public_Service_Co
+AZ_S,AZ,WestConnect,WestConnect_South,WECC_SW,western,Arizona_Public_Service_Co
+NM_W,NM,WestConnect,WestConnect_South,WECC_SW,western,Public_Service_Co_of_New_Mexico
+NM_E,NM,SPP,SPP_South,SPP,eastern,SPP
+TX_EP,TX,WestConnect,WestConnect_South,WECC_SW,western,ERCOT
+TX_N,TX,ERCOT,ERCOT,ERCOT,texas,ERCOT
+TX_W,TX,ERCOT,ERCOT,ERCOT,texas,ERCOT
+TX_S,TX,ERCOT,ERCOT,ERCOT,texas,ERCOT
+TX_PAN,TX,SPP,SPP_South,SPP,eastern,SPP
+TX_SPP,TX,SPP,SPP_South,SPP,eastern,SPP
+TX_HOU,TX,ERCOT,ERCOT,ERCOT,texas,ERCOT
+TX_MISO,TX,MISO,MISO_South,MISO,eastern,MISO
+ND_SPP,ND,SPP,SPP_North,SPP,eastern,SPP
+ND_MISO,ND,MISO,MISO_North,MISO,eastern,MISO
+SD,SD,SPP,SPP_North,SPP,eastern,SPP
+NE,NE,SPP,SPP_North,SPP,eastern,SPP
+KS,KS,SPP,SPP_South,SPP,eastern,SPP
+OK,OK,SPP,SPP_South,SPP,eastern,SPP
+MN_N,MN,MISO,MISO_North,MISO,eastern,MISO
+MN_S,MN,MISO,MISO_North,MISO,eastern,MISO
+WI_W,WI,MISO,MISO_North,MISO,eastern,MISO
+WI_E,WI,MISO,MISO_North,MISO,eastern,MISO
+IA,IA,MISO,MISO_Central,MISO,eastern,MISO
+MO_SPP,MO,SPP,SPP_South,SPP,eastern,SPP
+MO_MISO,MO,MISO,MISO_Central,MISO,eastern,MISO
+MO_SE,MO,SERTP,SERTP,SERC_C,eastern,Associated_Electric_Coop_Inc
+AR_SPP,AR,SPP,SPP_South,SPP,eastern,SPP
+AR_MISO,AR,MISO,MISO_South,MISO,eastern,MISO
+LA,LA,MISO,MISO_South,MISO,eastern,MISO
+MI_UP,MI,MISO,MISO_North,MISO,eastern,MISO
+MI_LP,MI,MISO,MISO_North,MISO,eastern,MISO
+MI_PJM,MI,PJM,PJM_West,PJM,eastern,PJM
+IL_PJM,IL,PJM,PJM_West,PJM,eastern,PJM
+IL_MISO,IL,MISO,MISO_Central,MISO,eastern,MISO
+IN_PJM,IN,PJM,PJM_West,PJM,eastern,PJM
+IN_MISO,IN,MISO,MISO_Central,MISO,eastern,MISO
+KY_PJM,KY,PJM,PJM_East,PJM,eastern,PJM
+KY_MISO,KY,MISO,MISO_Central,MISO,eastern,Tennessee_Valley_Authority
+MS_MISO,MS,MISO,MISO_South,MISO,eastern,MISO
+MS_SE,MS,SERTP,SERTP,SERC_C,eastern,Tennessee_Valley_Authority
+TN,TN,SERTP,SERTP,SERC_C,eastern,Tennessee_Valley_Authority
+AL,AL,SERTP,SERTP,SERC_SE,eastern,Southern_Co_Services_Inc
+GA_N,GA,SERTP,SERTP,SERC_SE,eastern,Southern_Co_Services_Inc
+GA_S,GA,SERTP,SERTP,SERC_SE,eastern,Southern_Co_Services_Inc
+SC,SC,SERTP,SERTP,SERC_E,eastern,South_Carolina_Electric_and_Gas_Co
+NC_SE,NC,SERTP,SERTP,SERC_E,eastern,Duke_Energy_Progress_East
+NC_PJM,NC,PJM,PJM_East,SERC_E,eastern,PJM
+FL_N,FL,FRCC,FRCC,SERC_F,eastern,Seminole_Electric_Coop_Inc
+FL_S,FL,FRCC,FRCC,SERC_F,eastern,Seminole_Electric_Coop_Inc
+FL_SE,FL,FRCC,FRCC,SERC_F,eastern,Florida_Power_and_Light
+OH_N,OH,PJM,PJM_East,PJM,eastern,PJM
+OH_S,OH,PJM,PJM_East,PJM,eastern,PJM
+WV,WV,PJM,PJM_East,PJM,eastern,PJM
+VA_W,VA,PJM,PJM_East,PJM,eastern,PJM
+VA_E,VA,PJM,PJM_East,PJM,eastern,PJM
+PA_W,PA,PJM,PJM_East,PJM,eastern,PJM
+PA_E,PA,PJM,PJM_East,PJM,eastern,PJM
+MD,MD,PJM,PJM_East,PJM,eastern,PJM
+DE,DE,PJM,PJM_East,PJM,eastern,PJM
+NJ,NJ,PJM,PJM_East,PJM,eastern,PJM
+NY_W,NY,NYISO,NYISO,NPCC_NY,eastern,NYISO
+NY_E,NY,NYISO,NYISO,NPCC_NY,eastern,NYISO
+NY_NYC,NY,NYISO,NYISO,NPCC_NY,eastern,NYISO
+NY_LI,NY,NYISO,NYISO,NPCC_NY,eastern,NYISO
+VT,VT,ISONE,ISONE,NPCC_NE,eastern,ISONE
+NH,NH,ISONE,ISONE,NPCC_NE,eastern,ISONE
+MA,MA,ISONE,ISONE,NPCC_NE,eastern,ISONE
+CT,CT,ISONE,ISONE,NPCC_NE,eastern,ISONE
+RI,RI,ISONE,ISONE,NPCC_NE,eastern,ISONE
+ME,ME,ISONE,ISONE,NPCC_NE,eastern,ISONE
diff --git a/inputs/zones/zoneset_config.yaml b/inputs/zones/zoneset_config.yaml
new file mode 100644
index 00000000..520bb5c3
--- /dev/null
+++ b/inputs/zones/zoneset_config.yaml
@@ -0,0 +1,14 @@
+drop_single_county_reinforcement_cost:
+- z3109
+- PJMcounty
+- UTcounty
+- z2972
+drop_interfaces_missing_cost:
+- z3109
+- PJMcounty
+- UTcounty
+reeds2pras_unitsize_unconstrain_counties:
+- z3109
+- PJMcounty
+- UTcounty
+- z2972
\ No newline at end of file
diff --git a/postprocessing/input_plots.py b/postprocessing/input_plots.py
index e5b32f10..3005b9f1 100644
--- a/postprocessing/input_plots.py
+++ b/postprocessing/input_plots.py
@@ -556,7 +556,7 @@ def plot_existing_unitsize(
                 'ReEDS_generator_database_final_EIA-NEMS.csv',
             )
         )
-        dfunits['reeds_ba'] = dfunits.FIPS.str.strip('p').map(county2zone)
+        dfunits['r'] = dfunits.FIPS.str.strip('p').map(county2zone)
     else:
         dfunits = pd.read_csv(os.path.join(case, 'inputs_case', 'unitdata.csv'))
 
@@ -566,7 +566,7 @@ def plot_existing_unitsize(
         & (dfunits.RetireYear > year)
         & (dfunits.tech.isin(techs))
     ].copy()
-    dfplot['region'] = dfplot.reeds_ba.map(hierarchy[level])
+    dfplot['region'] = dfplot.r.map(hierarchy[level])
 
     ### Set up plot
     regions = hierarchy[level].unique()
diff --git a/postprocessing/plots/level_map.csv b/postprocessing/plots/level_map.csv
index bab54797..84d6eb9d 100644
--- a/postprocessing/plots/level_map.csv
+++ b/postprocessing/plots/level_map.csv
@@ -1,6 +1,5 @@
 raw,display
-county,County
-ba,Balancing Area
+r,Model Zones
 nercr,NERC regions
 transreg,Transmission Planning Region
 transgrp,Transmission Planning Subregion
@@ -13,4 +12,3 @@ usda_region,USDA (Biomass Supply Curve) Region
 h2ptcreg,Hydrogen Production Tax Credit Regions
 hurdlereg,Hurdle Regions
 ccreg,Capacity Credit Regions
-aggreg,Aggregated Regions
diff --git a/postprocessing/reValue/reValue.py b/postprocessing/reValue/reValue.py
index 064376b2..be6ef046 100644
--- a/postprocessing/reValue/reValue.py
+++ b/postprocessing/reValue/reValue.py
@@ -193,25 +193,12 @@ def get_prices():
         #Roll prices from CST to UTC (this will bring prices from end of year to beginning of year)
         for col in df_p_h_serv[s]:
             df_p_h_serv[s][col] = np.roll(df_p_h_serv[s][col], 6)
-        if sw_reg != 'ba':
-            #In this case, we need to map prices to bas
-            df_hier_red = df_hier[df_hier[sw_reg].isin(df_p_h_serv[s].columns)]
-            df_p_h_serv[s] = df_p_h_serv[s][df_hier_red[sw_reg].tolist()]
-            df_p_h_serv[s].columns = df_hier_red['ba'].tolist()
     return df_pq, df_q_load, df_p_h_serv
 
 def calculate_benchmarks():
     print('Calculating benchmark annual average prices and system-wide price profile')
     #Calculate annual load by region and total load
     load_ba = df_q_load.drop(columns=['h']).sum()
-    if sw_reg != 'ba':
-        #In this case, we need to map load_ba from aggreg to ba, incorrectly assuming equal load for all bas in the same aggreg
-        df_load_ba = df_hier[df_hier['aggreg'].isin(load_ba.index)].copy()
-        df_load_ba['load'] = df_load_ba['aggreg'].map(load_ba.to_dict())
-        df_load_ba['ba_count'] = df_load_ba.groupby('aggreg')['ba'].transform('count')
-        df_load_ba['load'] = df_load_ba['load'] / df_load_ba['ba_count']
-        df_load_ba = df_load_ba.set_index('ba')
-        load_ba = df_load_ba['load']
     load_nat = load_ba.sum()
     #Calculate benchmark prices, assuming flat-block benchmark providing energy and firm capacity only,
     #so averages across time are simply time-weighted. But when averaging across space, we weight by load.
@@ -282,7 +269,7 @@ def calculate_metrics():
     print('Reducing profiles to only those that can be mapped to prices')
     #First find list of BAs associated with ReEDS run
     reg_set = df_pq['reeds_ba'].unique().tolist()
-    bas =  reg_set if sw_reg == 'ba' else df_hier[df_hier[sw_reg].isin(reg_set)]['ba'].tolist()
+    bas = reg_set
     df_p_h_s = df_p_h_serv.copy() #Shallow copy so we don't duplicate so much data
     if r['meta_path'] != 'none':
         df_meta = df_meta_full[df_meta_full['reeds_ba'].isin(bas)].copy()
@@ -367,12 +354,12 @@ def calculate_metrics():
     reeds_run_path = r['reeds_run_path'].replace('"', '')
     year = r['year']
     switches = reeds.io.get_switches(reeds_run_path)
-    sw_reg = switches['GSw_RegionResolution']
-    hier_file = f'{this_dir_path}/../../inputs/zones/{switches.GSw_ZoneSet}/hierarchy_from134.csv'
-    df_hier = pd.read_csv(hier_file, usecols=['ba',sw_reg]).drop_duplicates()
     df_hier_run = pd.read_csv(f'{reeds_run_path}/inputs_case/hierarchy.csv')
-    df_county_map = pd.read_csv(hier_file, usecols=['county','ba'])
-    df_county_map.columns = ['reeds_county', 'reeds_ba']
+    df_county_map = (
+        reeds.io.get_county2zone(reeds_run_path, as_map=False)
+        .rename(columns={'county': 'reeds_county', 'r': 'reeds_ba'})
+        [['reeds_county', 'reeds_ba']]
+    )
     df_hmap = pd.read_csv(f'{reeds_run_path}/inputs_case/rep/hmap_myr.csv')
     #Only fetch prices if we haven't already for this reeds run and year
     #TODO: Include tech here in the dct_prices tuple key? For now I disallow multiple techs
diff --git a/postprocessing/retail_rate_module/calculate_historical_capex.py b/postprocessing/retail_rate_module/calculate_historical_capex.py
index 9b8e4df7..dc1ac09a 100644
--- a/postprocessing/retail_rate_module/calculate_historical_capex.py
+++ b/postprocessing/retail_rate_module/calculate_historical_capex.py
@@ -13,10 +13,8 @@
 import reeds
 
 def get_historical_units(inputs_case):
-    # Read generator database and map units to the model regions for this run
-    r_county = pd.read_csv(os.path.join(inputs_case, 'r_county.csv'))
+    # Read generator database
     gendb = pd.read_csv(os.path.join(inputs_case, 'unitdata.csv'), low_memory=False)
-    gendb = gendb.merge(r_county, left_on='FIPS', right_on='county', how='left')
 
     # Select units existing before or during the model start year
     sw = reeds.io.get_switches(inputs_case)
diff --git a/postprocessing/tableau/tableau_viz_suite.py b/postprocessing/tableau/tableau_viz_suite.py
index 36ce1b86..b469b83c 100644
--- a/postprocessing/tableau/tableau_viz_suite.py
+++ b/postprocessing/tableau/tableau_viz_suite.py
@@ -8,6 +8,7 @@
 import datetime
 from lxml import etree as ET
 import shutil
+from pathlib import Path
 pd.options.display.max_rows = 20
 pd.options.display.max_columns = 200
 
@@ -90,7 +91,6 @@ def create_scenarios_csv(output_dir,cases):
 def produce_hierarchy_file(output_dir,basecase):
     
     hierarchy = reeds.io.get_hierarchy(cases[basecase])
-    sw = reeds.io.get_switches(cases[basecase])
 
     # hierarchy.csv has machine readable names - convert them to values from level_map
     for col in hierarchy.columns:
@@ -100,28 +100,15 @@ def produce_hierarchy_file(output_dir,basecase):
     # clean up region names, ex. turn 'NorthernGrid_West' to 'NorthernGrid West', replace all instances of '_' with ' ' in the entire dataframe
     hierarchy = hierarchy.replace('_',' ',regex=True)
 
-    if sw.GSw_RegionResolution == "county" or sw.GSw_RegionResolution == "mixed":
-        # county2zone has the county FIPS to ReEDS BA mapping
-        county2zone = pd.read_csv(os.path.join(reeds_path, 'inputs', 'county2zone.csv'), dtype={'FIPS':str},)
-        county2zone['Region'] = 'p' + county2zone.FIPS
-        # Add BA info to hierarchy
-        hierarchy = hierarchy.merge(county2zone.drop(columns=['state']), left_on='r', right_on='Region')
-        # move the FIPS column to be the first column in the df
-        hierarchy = hierarchy[['Region'] + [col for col in hierarchy.columns if col != 'Region']]
-        # export
-        hierarchy.to_csv(os.path.join(output_dir,'shapefiles','hierarchy.csv'),index=False)
-    elif sw.GSw_RegionResolution == 'aggreg' or sw.GSw_RegionResolution == 'ba':
-        # add columns to match the county-level hierarchy.csv format
-        hierarchy = hierarchy.reset_index()
-        hierarchy['ba'] = hierarchy['r']
-        hierarchy = hierarchy.rename(columns={'r':'Region'})
-        hierarchy['FIPS'] = '' # add a blank FIPS column so that the hierarchy.csv has the same columns as when using county-level runs
-        hierarchy['county_name'] = '' # add a blank county_name column so that the hierarchy.csv has the same columns as when using county-level runs
-        # then hierarchy.csv is already ready to export 
-        hierarchy.to_csv(os.path.join(output_dir,'shapefiles','hierarchy.csv'),index=False)
-    else:
-        print('All levels must be either county or ba now, all aggregation will be done via a hierarchy mapping.')
-        pass
+    # add columns to match the county-level hierarchy.csv format
+    # (required due to legacy downstream handling of counties)
+    hierarchy = hierarchy.reset_index()
+    hierarchy['ba'] = hierarchy['r']
+    hierarchy = hierarchy.rename(columns={'r':'Region'})
+    hierarchy['FIPS'] = '' # add a blank FIPS column so that the hierarchy.csv has the same columns as when using county-level runs
+    hierarchy['county_name'] = '' # add a blank county_name column so that the hierarchy.csv has the same columns as when using county-level runs
+    # then hierarchy.csv is already ready to export 
+    hierarchy.to_csv(os.path.join(output_dir,'shapefiles','hierarchy.csv'),index=False)
     
     return
 
@@ -155,51 +142,27 @@ def produce_transmission_endpoints():
     os.mkdir(os.path.join(output_dir,'shapefiles','transmission_endpoints'))
     
     try:
-        if dictin_sw[basecase].GSw_RegionResolution == "county" or dictin_sw[basecase].GSw_RegionResolution == "mixed":
-            
-            src_file  = os.path.join(reeds_path,'inputs','shapefiles','US_COUNTY_2022','US_COUNTY_2022.shp')
-            dst_file  = os.path.join(output_dir,'shapefiles','transmission_endpoints','transmission_endpoints.shp')
-
-            # Read the shapefile
-            gdf = gpd.read_file(src_file)
-
-            # Compute centroids
-            gdf['geometry'] = gdf.geometry.centroid
-
-            # add 'BA' column to this shapefile, needed for the Tableau join
-            # county2zone has the county FIPS to ReEDS BA mapping, must be the mapping from the ReEDS repo not inputs_case (which does not have all regions if not running nationally)
-            county2zone = pd.read_csv(os.path.join(reeds_path,'inputs','county2zone.csv'), dtype={'FIPS':str},index_col='FIPS').squeeze(1)
-
-            gdf['BA'] = gdf['FIPS'].map(lambda x: county2zone['ba'][x])
-
-            # rename for join in Tableau
-            gdf = gdf.rename(columns={'rb':'Region'})
-
-            # Export to shapefile
-            gdf.to_file(dst_file)
-        else:
-            src_file  = os.path.join(reeds_path,'inputs','shapefiles','transmission_endpoints','transmission_endpoints.shp')
-            dst_file  = os.path.join(output_dir,'shapefiles','transmission_endpoints','transmission_endpoints.shp')
-
-            gdf = reeds.io.get_zonemap(cases[basecase]).reset_index().rename(columns={'index':'Region',
-                                                                                    'country':'COUNTRY',
-                                                                                    'st':'STATE',})
-            # columns we have: ['geometry', 'node_longitude', 'node_latitude', 'x', 'y', 'offshore', 'centroid_x', 'centroid_y', 'km2', 'aggreg', 'nercr', 'transreg', 'transgrp', 'cendiv', 'st', 'interconnect', 'country', 'usda_region', 'h2ptcreg', 'hurdlereg'],
-            # columns we need: ['Region', 'FIPS', 'NAME', 'NAMELSAD', 'COUNTYFP', 'STATE', 'STCODE', 'STATEFP', 'COUNTRY', 'BA', 'geometry']
-            gdf['geometry'] = gpd.points_from_xy(gdf['x'], gdf['y'])
-            gdf['BA'] = gdf['Region']
-
-            # only keep columns needed for Tableau join
-            keep_cols = ['Region','STATE','COUNTRY','BA','geometry']
-            gdf = gdf[keep_cols]
-
-            # add blank columns (ideally these would be populated correctly or removed but they are not used in the merge)
-            for col in ['FIPS', 'NAME', 'NAMELSAD', 'COUNTYFP', 'STATE', 'STCODE', 'STATEFP', 'COUNTRY']:
-                # if that column is not in the gdf, add it as a blank column
-                if col not in gdf.columns:
-                    gdf[col] = ''
-
-            gdf.to_file(dst_file)
+        dst_file  = os.path.join(output_dir,'shapefiles','transmission_endpoints','transmission_endpoints.shp')
+
+        gdf = reeds.io.get_zonemap(cases[basecase]).reset_index().rename(columns={'index':'Region',
+                                                                                'country':'COUNTRY',
+                                                                                'st':'STATE',})
+        # columns we have: ['geometry', 'node_longitude', 'node_latitude', 'x', 'y', 'offshore', 'centroid_x', 'centroid_y', 'km2', 'aggreg', 'nercr', 'transreg', 'transgrp', 'cendiv', 'st', 'interconnect', 'country', 'usda_region', 'h2ptcreg', 'hurdlereg'],
+        # columns we need: ['Region', 'FIPS', 'NAME', 'NAMELSAD', 'COUNTYFP', 'STATE', 'STCODE', 'STATEFP', 'COUNTRY', 'BA', 'geometry']
+        gdf['geometry'] = gpd.points_from_xy(gdf['x'], gdf['y'])
+        gdf['BA'] = gdf['Region']
+
+        # only keep columns needed for Tableau join
+        keep_cols = ['Region','STATE','COUNTRY','BA','geometry']
+        gdf = gdf[keep_cols]
+
+        # add blank columns (ideally these would be populated correctly or removed but they are not used in the merge)
+        for col in ['FIPS', 'NAME', 'NAMELSAD', 'COUNTYFP', 'STATE', 'STCODE', 'STATEFP', 'COUNTRY']:
+            # if that column is not in the gdf, add it as a blank column
+            if col not in gdf.columns:
+                gdf[col] = ''
+
+        gdf.to_file(dst_file)
     except Exception as error:
         print(error)
 
@@ -295,26 +258,11 @@ def reformat(df,case,metric,years):
                 df['Transmission Planning Subregion End'] = df['Transmission Planning Subregion End'].str.replace("_"," ") # turn NorthernGrid_West to 'NorthernGrid West'
                 df['Transmission Planning Subregion Begin'] = df['Transmission Planning Subregion Begin'].str.replace("_"," ")
 
-        if sw.GSw_RegionResolution == "county":
-            # the 'r' column already has the 'p41003' format
-            df = df.rename(columns={'r':'County'})
-            # add a column with the FIPS code (remove the 'p' prefix and turn the value into a integer from the CountyName column)
-            df['FIPS'] = df['County'].str.replace('p','').astype(int)
-
-            # now need to aggregate up to BA level, county2zone has the county FIPS to ReEDS BA mapping
-            county2zone = pd.read_csv(os.path.join(cases[case], 'inputs_case', 'county2zone.csv'), dtype={'FIPS':int},index_col='FIPS').squeeze(1)
-
-            # aggregate up to BA level using the hierarchy mapping
-            df['BA'] = df['FIPS'].map(lambda x: county2zone['ba'][x])
-            del df['FIPS']
-        elif sw.GSw_RegionResolution == 'aggreg' or sw.GSw_RegionResolution == 'ba':
-            # the 'r' column already has the 'p4' BA format
-            df = df.rename(columns={'r':'BA'})
-            # make the county column blank as it will not be used when we are using BA-level runs
-            df['County']=''
-        else:
-            print('All levels must be either county or ba now, all aggregation will be done via a hierarchy mapping.')
-            pass
+        # the 'r' column already has the 'p4' BA format
+        df = df.rename(columns={'r':'BA'})
+        # make the county column blank as it will not be used when we are using BA-level runs
+        # (required due to legacy downstream handling of counties)
+        df['County']=''
 
         # add a column named 'Metric' which helps in the Tableau union
         df.loc[:,'Metric'] = metric
@@ -417,7 +365,7 @@ def calc_peakload(
     ).rename(columns=int)
 
     dictout = {}
-    level_map = reeds.results.get_level_map(case)
+    level_map = reeds.results.get_level_map()
     for level in levels:
         df_level = df.loc[level,years].stack().rename_axis(['r','t']).rename('Value').reset_index().astype({'t':int}).set_index(['r','t']).squeeze().reset_index()
         df_level['Spatial Resolution'] = level_map[level]
@@ -531,7 +479,7 @@ def export(dictin,output_dir):
     parser.add_argument(
         '--levels', 
         nargs="+",     # '+' means one or more arguments
-        default=['r'], # this can be 'ba','county','aggreg', depending on the run
+        default=['r'],
         help="Spatial resolution for results")
     parser.add_argument(
         '--trans_level', type=str, default='transgrp',
@@ -602,7 +550,7 @@ def export(dictin,output_dir):
     create_scenarios_csv(output_dir,cases)
 
     # Grab clean display names for the levels
-    level_map = reeds.results.get_level_map(cases[basecase])
+    level_map = reeds.results.get_level_map()
 
     # import some key inputs from ReEDS
     dictin_sw = {case: reeds.io.get_switches(cases[case]) for case in cases}
diff --git a/reeds/input_processing/WriteHintage.py b/reeds/input_processing/WriteHintage.py
index 755993d1..6d8cb071 100644
--- a/reeds/input_processing/WriteHintage.py
+++ b/reeds/input_processing/WriteHintage.py
@@ -327,18 +327,11 @@ def main(reeds_path, inputs_case):
                     ]
     }
 
-    # Import mapping files
-    r_county = pd.read_csv(
-        os.path.join(inputs_case,'r_county.csv'), index_col='county').squeeze(1)
-
     # Import generator database
     indat = pd.read_csv(os.path.join(inputs_case,'unitdata.csv'),
                         low_memory=False
     )
 
-    # Map counties to modeled regions
-    indat['r'] = indat.FIPS.map(r_county)
-
     # Apply inflation to VOM costs
     indat['T_VOM'] *= inflator
     indat['T_CCSV'] = indat.T_VOM + inflator * indat.T_CCSV
diff --git a/reeds/input_processing/copy_files.py b/reeds/input_processing/copy_files.py
index 5a74bdfa..efcf21b1 100644
--- a/reeds/input_processing/copy_files.py
+++ b/reeds/input_processing/copy_files.py
@@ -41,7 +41,7 @@ def is_required_file(runfiles_row, sw):
     return is_required
 
 
-def read_runfiles(reeds_path, inputs_case, sw, agglevel_variables):
+def read_runfiles(reeds_path, sw):
     """
     Read runfiles.csv and return the runfiles dataframe
     Identify files that have a region index versus those that do not.
@@ -64,50 +64,20 @@ def read_runfiles(reeds_path, inputs_case, sw, agglevel_variables):
         args=(sw,),
     )
 
-    # If a filepath isn't specified, that means it is already in the
-    # inputs_case folder, otherwise use the filepath
-    # We leave the 'lvl' portion of 'full_filepath' unformatted because
-    # we may need to read multiple 'lvl' variants of the file at once later
-    runfiles['full_filepath'] = runfiles.apply(
-        axis=1,
-        func=lambda row: os.path.join(inputs_case, row['filename'])
-        if pd.isna(row['filepath'])
-        else os.path.join(reeds_path, row['filepath'].format(**{**sw, **{'lvl': '{lvl}'}}))
-    )
-
-    # Create a copy of runfiles that specifies the 'lvl' that applies to each file
-    # (only used to determine missing files, the original runfiles is used later).
-    # In general, the 'lvl' corresponds to GSw_RegionResolution.
-    # For mixed resolution, each 'lvl'-indexed file is split into two rows -
-    # one for the BA-level file and the other for the county-level file.
-    runfiles_with_lvls = runfiles.assign(lvl='')
-    lvl_indexed_file_mask = (
-        (runfiles_with_lvls.filepath.notna())
-        & (runfiles_with_lvls.filepath.str.contains('{lvl}'))
-    )
-    if agglevel_variables['lvl'] == 'mult':
-        runfiles_with_lvls.loc[lvl_indexed_file_mask, 'lvl'] = 'ba,county'
-        runfiles_with_lvls['lvl'] = runfiles_with_lvls['lvl'].str.split(',')
-        runfiles_with_lvls = runfiles_with_lvls.explode('lvl')
-    else:
-        runfiles_with_lvls.loc[lvl_indexed_file_mask, 'lvl'] = agglevel_variables['lvl']
-
     # Determine existence of each file
-    runfiles_with_lvls['full_filepath'] = runfiles_with_lvls.apply(
+    runfiles['full_filepath'] = runfiles.apply(
         axis=1,
-        func=lambda x: x['full_filepath'].format(**{'lvl': x['lvl']})
+        func=lambda row: os.path.join(reeds_path, row['filepath'].format(**sw))
     )
-    runfiles_with_lvls['file_exists'] = (
-        runfiles_with_lvls['full_filepath'].apply(lambda x: os.path.exists(x))
+    runfiles['file_exists'] = (
+        runfiles['full_filepath'].apply(lambda x: os.path.exists(x))
     )
 
-    # Raise an error if any of the required files with specified filepaths are missing
-    missing_required_files = list(
-        runfiles_with_lvls.loc[(
-            runfiles_with_lvls['file_is_required']
-            & ~runfiles_with_lvls['file_exists']
-            & ~runfiles_with_lvls['filepath'].isna()
-        )]['filepath']
+    # Raise an error if any of the required files are missing
+    missing_required_files = (
+        runfiles.loc[runfiles['file_is_required'] & ~runfiles['file_exists']]
+        ['filepath']
+        .tolist()
     )
     if len(missing_required_files) > 0:
         raise FileNotFoundError(
@@ -116,15 +86,6 @@ def read_runfiles(reeds_path, inputs_case, sw, agglevel_variables):
             .format('\n'.join(missing_required_files))
         )
 
-    # Add file existence information to runfiles (for lvl-indexed files, the file must exist
-    # at all resolutions required for the run).
-    # We have to add this to runfiles rather than using runfiles_with_lvls because later
-    # sections require the 'lvl' placeholder in the filename to be unformatted and the file
-    # to be represented by one row rather than the multiple split up rows in runfiles_with_lvls.
-    runfiles['file_exists'] = (
-        runfiles['filename'].map(runfiles_with_lvls.groupby('filename')['file_exists'].min())
-    )
-
     # Non-region files that need copied either do not have an entry in region_col
     # or have 'ignore' as the entry. They also have a filepath specified.
     non_region_files = (
@@ -193,20 +154,24 @@ def get_regions_and_agglevel(
     """
     sw = reeds.io.get_switches(inputs_case)
 
-    ## TEMPORARY 20260402: Load the full regions list
-    ## Use the line below once we make the switch
-    # hierarchy = reeds.io.assemble_hierarchy(inputs_case)
-    hierarchy = pd.read_csv(
-        Path(reeds.io.reeds_path, 'inputs', 'zones', sw.GSw_ZoneSet, 'hierarchy_from134.csv')
-    )
+    hierarchy = reeds.io.assemble_hierarchy(inputs_case, extra=False)
     hierarchy['offshore'] = 0
-    # Append offshore zones if using
+    # Label offshore zones if using
     if int(sw.GSw_OffshoreZones):
-        hierarchy_offshore = reeds.io.assemble_hierarchy(
-            fpath=os.path.join(reeds_path, 'inputs', 'zones', 'hierarchy_offshore.csv'),
-            extra=False,
-        ).assign(offshore=1)
-        hierarchy = pd.concat([hierarchy, hierarchy_offshore], ignore_index=True)
+        offshore_zones = (
+            reeds.io.assemble_hierarchy(
+                fpath=os.path.join(
+                    reeds_path,
+                    'inputs',
+                    'zones',
+                    'hierarchy_offshore.csv'
+                ),
+                extra=False,
+            )
+            ['ba']
+            .tolist()
+        )
+        hierarchy.loc[hierarchy.r.isin(offshore_zones), 'offshore'] = 1
 
     # Save the original hierarchy file: used in recf.py and hourly_*.py scripts
     if save_regions_and_agglevel:
@@ -216,9 +181,8 @@ def get_regions_and_agglevel(
             )
 
     # Add a row for each county
-    ## TEMPORARY 20260402: Use the old 134-zone county2zone until the aggregation approach is updated
     county2zone = (
-        reeds.io.get_county2zone(GSw_ZoneSet='z134', as_map=False)
+        reeds.io.get_county2zone(GSw_ZoneSet=sw['GSw_ZoneSet'], as_map=False)
         .rename(columns={'r':'ba'})
     )
     county2zone['county'] = 'p' + county2zone.FIPS
@@ -228,7 +192,19 @@ def get_regions_and_agglevel(
     )
 
     # Add county info to hierarchy
-    hierarchy = hierarchy.merge(county2zone.drop(columns=['FIPS','state']), on='ba', how='outer')
+    hierarchy = hierarchy.merge(
+        county2zone.drop(columns=['FIPS','state']),
+        left_on='r',
+        right_on='ba',
+        how='outer'
+    )
+
+    # Add legacy zone (z134) info to hierarchy
+    # This is needed because some inputs still have data at z134 resolution,
+    # so we need to capture these legacy zones when subsetting to valid regions
+    county2zone_z134 = reeds.io.get_county2zone(GSw_ZoneSet='z134', as_map=True)
+    county2zone_z134.index = 'p' + county2zone_z134.index
+    hierarchy['legacy_ba'] = hierarchy['county'].map(county2zone_z134)
 
     # Subset hierarchy for the region of interest (based on the GSw_Region switch)
     # Parse the GSw_Region switch. If it includes a '/' character, it has the format
@@ -247,43 +223,8 @@ def get_regions_and_agglevel(
 
         hier_sub = pd.concat([hier_sub, hier_sub_partial])
 
-    # Read region resolution switch to determine agglevel
-    agglevel = sw['GSw_RegionResolution'].lower()
-
-    # Check if desired spatial resolution is mixed
-    if agglevel == 'mixed':
-        #Set value in resolution column of hier_sub to match value assigned in modeled_regions.csv
-        region_def = pd.read_csv(
-            os.path.join(reeds_path,'inputs','userinput','modeled_regions.csv')
-        )[['r', sw.GSw_ZoneSet]]
-
-        res_map = region_def.set_index('r').squeeze(1).to_dict()
-        hier_sub['resolution'] = hier_sub['ba'].map(res_map)
-    else:
-        hier_sub['resolution'] = agglevel
-
-
-    # Write out all unique aggregation levels present in the hierarchy resolution column
-    agglevels = hier_sub['resolution'].unique()
-
-    # Write agglevel
-    if save_regions_and_agglevel:
-        pd.DataFrame(agglevels, columns=['agglevels']).to_csv(
-            os.path.join(inputs_case, 'agglevels.csv'), index=False)
-
-
-    # Create an r column at the front of the dataframe and populate it with the
-    # county-level regions (overwritten if needed)
-    hier_sub.insert(0,'r',hier_sub['county'])
-
-    # Overwrite the regions with the ba, state, or aggreg values as specififed
-    for level in ['ba','aggreg']:
-        hier_sub.loc[hier_sub['resolution'] == level, 'r'] = (
-            hier_sub.loc[hier_sub['resolution'] == level, level])
-
     # Write out mappings of r and ba to all counties
     r_county = hier_sub[['r','county']].dropna(subset='county')
-    ba_county = hier_sub[['ba','county']]
 
     # Rewrite county2zone for this case
     county2zone_agg = county2zone.merge(r_county, on='county')
@@ -296,23 +237,10 @@ def get_regions_and_agglevel(
         r_county.to_csv(
             os.path.join(inputs_case, 'r_county.csv'), index=False)
 
-        # Write out a mapping of r to ba regions
-        hier_sub[['r','ba']].drop_duplicates().to_csv(
-            os.path.join(inputs_case, 'r_ba.csv'), index=False)
         # Write out mapping of r to census divisions
         hier_sub[['r','cendiv']].drop_duplicates().to_csv(
             os.path.join(inputs_case, 'r_cendiv.csv'), index=False)
 
-        # Write out mapping of rb to aggreg (for writesupplycurves.py)
-        hier_sub[['ba','aggreg']].drop_duplicates().to_csv(
-            os.path.join(inputs_case, 'rb_aggreg.csv'), index=False)
-
-        # Write out val_county and val_ba before collapsing to unique regions
-        hier_sub['county'].dropna().to_csv(
-            os.path.join(inputs_case, 'county.csv'), header=False, index=False)
-        hier_sub['ba'].drop_duplicates().to_csv(
-            os.path.join(inputs_case, 'val_ba.csv'), header=False, index=False)
-
     # Find all the unique elements that might define a region
     val_r_all = []
     for column in hier_sub.columns.drop('offshore', errors='ignore'):
@@ -325,12 +253,8 @@ def get_regions_and_agglevel(
         pd.Series(val_r_all).to_csv(
             os.path.join(inputs_case, 'val_r_all.csv'), header=False, index=False)
 
-    # Rename columns and save as hierarchy_with_res.csv for use in agglevel_variables function
-    hier_sub.drop(columns='offshore', errors='ignore').rename(columns={'r':'*r'}).to_csv(
-        os.path.join(inputs_case, 'hierarchy_with_res.csv'), index=False)
-
     # Drop county name and resolution columns
-    hier_sub = hier_sub.drop(['county_name','resolution'],axis=1)
+    hier_sub = hier_sub.drop(['county_name'],axis=1)
 
 
     # Collapse to only unique regions
@@ -341,18 +265,8 @@ def get_regions_and_agglevel(
     hier_sub['numeric_value'] = hier_sub['r'].str.extract('(\d+)').astype(float)
     hier_sub = hier_sub.sort_values(by='numeric_value').drop('numeric_value', axis=1)
 
-    # Output the itlgrp files for mixed and county resolution
-
-    if sw.GSw_RegionResolution == 'aggreg':
-        hier_sub['itlgrp'] = hier_sub['aggreg']
-    else:
-        hier_sub['itlgrp'] = hier_sub['ba']
-
-    if sw.GSw_RegionResolution == 'mixed':
-        mod_reg = pd.read_csv(
-            os.path.join(reeds_path,'inputs','userinput','modeled_regions.csv'))
-        if 'aggreg' in mod_reg[sw.GSw_ZoneSet].tolist():
-            hier_sub['itlgrp'] = hier_sub['aggreg']
+    ### TEMPORARY 20260402: For now just assign 'itlgrp' hierarchy level to 'r'
+    hier_sub['itlgrp'] = hier_sub['r']
     hier_sub[['r','itlgrp']].rename(columns={'r':'*r'}).to_csv(
         os.path.join(inputs_case, 'hierarchy_itlgrp.csv'), index=False)
 
@@ -374,7 +288,6 @@ def get_regions_and_agglevel(
     # Note the conversion to a pd Series is necessary to leverage the to_csv function
     if save_regions_and_agglevel:
         comments = {
-            'aggreg': 'aggregated region',
             'cendiv': 'census division',
             'country': 'nation',
             'h2ptcreg': 'H2 production tax credit region',
@@ -403,7 +316,7 @@ def get_regions_and_agglevel(
         (
             hier_sub
             .rename(columns={'r':'*r'})
-            .drop(columns=['aggreg','offshore'], errors='ignore')
+            .drop(columns=['legacy_ba', 'offshore'], errors='ignore')
         ).to_csv(os.path.join(inputs_case, 'hierarchy.csv'), index=False)
 
         # Write offshore zones
@@ -430,7 +343,6 @@ def get_regions_and_agglevel(
         "val_r_all": val_r_all,
         "val_st": val_st,
         "r_county": r_county,
-        "ba_county": ba_county,
         "levels": levels
     }
 
@@ -507,7 +419,6 @@ def read_banned_tech_file(full_path, filepath, inputs_case, r_county):
 def subset_to_valid_regions(
     sw,
     region_file_entry,
-    agglevel_variables,
     regions_and_agglevel,
     inputs_case=None,
     agg=True,
@@ -531,145 +442,55 @@ def subset_to_valid_regions(
     region_col = region_file_entry['region_col']
     fix_cols = [i for i in region_file_entry['fix_cols'].split(',') if i != '']
 
-    sc_point_gid_index = False
-    if (
-        filename.startswith('supplycurve')
-        or filename.startswith('exog_cap')
-        or filename.startswith('prescribed_builds')
-    ):
-        sc_point_gid_index = True
-
-    # When running at mixed resolution we need to copy both ba and county resolution data
-    if (agglevel_variables['lvl'] == 'mult') and ('lvl' in filepath) and (not sc_point_gid_index):
-        full_path_ba = full_path.replace('{lvl}', 'ba')
-        full_path_county = full_path.replace('{lvl}', 'county')
-        match filetype_in:
-            case 'h5':
-                df_ba = reeds.io.read_file(full_path_ba, parse_timestamps=True)
-                df_county = reeds.io.read_file(full_path_county, parse_timestamps=True)
-            case 'csv':
-                df_ba = pd.read_csv(
-                    full_path_ba,
-                    dtype={'FIPS':str, 'fips':str, 'cnty_fips':str}, comment='#',
-                )
-                df_county = pd.read_csv(
-                    full_path_county,
-                    dtype={'FIPS':str, 'fips':str, 'cnty_fips':str}, comment='#',
-                )
-            case _:
-                raise TypeError(f'filetype for {full_path} is not .csv or .h5')
-
-    # Single resolution procedure
-    else:
-        # Replace '{switchnames}' in full_path with corresponding switch values
-        full_path = full_path.format(**{**sw, **{'lvl':agglevel_variables['lvl']}})
-        ## Filename conditions
-        if filename.startswith('supplycurve'):
-            df = reeds.io.assemble_supplycurve(
-                full_path,
-                case=os.path.dirname(os.path.normpath(inputs_case)),
-                agg=agg,
-            ).reset_index()
-        elif filename.startswith('exog_cap'):
-            df = reeds.io.assemble_exog_cap(
-                full_path,
-                case=os.path.dirname(os.path.normpath(inputs_case)),
-            )
-        elif filename.startswith('prescribed_builds'):
-            df = reeds.io.assemble_prescribed_builds(
-                full_path,
-                case=os.path.dirname(os.path.normpath(inputs_case)),
-            )
-        elif filename == 'techs_banned.csv':
-            df, nuclear_ban_regions = read_banned_tech_file(
-                full_path,
-                filepath,
-                inputs_case,
-                r_county=regions_and_agglevel['r_county']
-            )
-            nuclear_ban_regions.to_csv(
-                os.path.join(inputs_case,'nuclear_ba_ban_list.csv'),
-                index=False
-            )
-        ## Filetype conditions
-        elif filetype_in == 'h5':
-            df = reeds.io.read_file(full_path, parse_timestamps=True)
-        elif filetype_in == 'csv':
-            df = pd.read_csv(full_path, dtype={'FIPS':str, 'fips':str, 'cnty_fips':str}, comment='#')
-        else:
-            raise ValueError(f'Unmatched filename ({filename}) or filetype ({filetype_in})')
-
-    # ---- Filter data to valid regions ----
-    # If running at mixed resolution we need to remove BA level data for regions that are being solved at county resolution
-    if (agglevel_variables['lvl'] == 'mult') and ('lvl' in filepath) and (not sc_point_gid_index):
-        hier = pd.read_csv(os.path.join(inputs_case,'hierarchy_with_res.csv')).rename(columns = {'*r':'r'})
-        # Filter function parameters to only include BA resolution regions
-        valid_regions_ba = {level: list(hier[hier['r']
-                                .isin(agglevel_variables['ba_regions'])][level].unique()) for level in levels}
-        val_st_ba = valid_regions_ba['st']
-        val_r_all_ba = []
-        for value in valid_regions_ba.values():
-            val_r_all_ba.extend(value)
-        val_r_all_ba = list(set(val_r_all_ba))
-        # Add BA regions associated with states and aggregs being run at BA resolution
-        val_r_all_ba.extend(x for x in agglevel_variables['ba_regions']if x not in val_r_all_ba)
-        df_ba = filter_data(
-            df_ba,
-            region_col,
-            fix_cols,levels,
-            val_r_all=val_r_all_ba,
-            valid_regions=valid_regions_ba,
-            val_st=val_st_ba,
-            filename=filename
+    # Replace '{switchnames}' in full_path with corresponding switch values
+    full_path = full_path.format(**sw)
+    ## Filename conditions
+    if filename.startswith('supplycurve'):
+        df = reeds.io.assemble_supplycurve(
+            full_path,
+            case=os.path.dirname(os.path.normpath(inputs_case)),
+            agg=agg,
+        ).reset_index()
+    elif filename.startswith('exog_cap'):
+        df = reeds.io.assemble_exog_cap(
+            full_path,
+            case=os.path.dirname(os.path.normpath(inputs_case)),
         )
-        # Filter function parameters to only include county resolution regions
-        valid_regions_county = {level: (hier[hier['r']
-                                .isin(agglevel_variables['county_regions'])][level].unique()) for level in levels}
-        val_st_county = valid_regions_county['st']
-        val_r_all_county = []
-        for value in valid_regions_county.values():
-            val_r_all_county.extend(value)
-        val_r_all_county = list(dict.fromkeys(val_r_all_county))
-
-        df_county = filter_data(
-            df_county,
-            region_col,
-            fix_cols,
-            levels,
-            val_r_all=val_r_all_county,
-            valid_regions=valid_regions_county,
-            val_st=val_st_county,
-            filename=filename
+    elif filename.startswith('prescribed_builds'):
+        df = reeds.io.assemble_prescribed_builds(
+            full_path,
+            case=os.path.dirname(os.path.normpath(inputs_case)),
         )
-
-        # Combine BA and county data
-        # The filter data function returns a dataframe with NAN values to prevent empty H5 files
-        # If either the BA data or county data are populated we can drop the nan data
-        if df_county.isna().all().all() and not df_ba.isna().all().all():
-            df = df_ba
-        elif not df_county.isna().all().all() and df_ba.isna().all().all():
-            df = df_county
-        else:
-            # Combine BA and county data
-            if region_file_entry['wide'] == 1 :
-                df = pd.concat([df_ba,df_county],axis =1)
-            else:
-                df = pd.concat([df_ba,df_county])
-
-    # Single resolution procedure
-    # Or procedure for input data that exist at single resolution and
-    # are aggregated/disaggregated later
-    else:
-        df = filter_data(
-            df,
-            region_col,
-            fix_cols,
-            levels,
-            val_r_all,
-            valid_regions,
-            val_st,
-            filename=filename
+    elif filename == 'techs_banned.csv':
+        df, nuclear_ban_regions = read_banned_tech_file(
+            full_path,
+            filepath,
+            inputs_case,
+            r_county=regions_and_agglevel['r_county']
+        )
+        nuclear_ban_regions.to_csv(
+            os.path.join(inputs_case,'nuclear_ba_ban_list.csv'),
+            index=False
         )
+    ## Filetype conditions
+    elif filetype_in == 'h5':
+        df = reeds.io.read_file(full_path, parse_timestamps=True)
+    elif filetype_in == 'csv':
+        df = pd.read_csv(full_path, dtype={'FIPS':str, 'fips':str, 'cnty_fips':str}, comment='#')
+    else:
+        raise ValueError(f'Unmatched filename ({filename}) or filetype ({filetype_in})')
+
+    # Filter data to valid regions
+    df = filter_data(
+        df,
+        region_col,
+        fix_cols,
+        levels,
+        val_r_all,
+        valid_regions,
+        val_st,
+        filename=filename
+    )
 
     return df
 
@@ -947,31 +768,28 @@ def write_non_region_files(non_region_files, sw, inputs_case, regions_and_agglev
             )
 
     
-def calculate_county_fractions(df, county2zone):
+def calculate_county_fractions(df, county2zone_with_legacy_bas):
     """
     Calculates the values associated with each county as a percentage
-    of the total values for the county's state, BA, and model region
-    (where "BA" means a zone from the set of default 134 zones and 
-    "model region" means a zone from the set of zones specific to this run).
-    Note the calculation of the county-to-BA fractions will eventually
+    of the total values for the county's state, zone, and legacy BA
+    (where "zone" means a region from the zone set corresponding to
+    the current run and "legacy BA" means a region from the z134 zone set).
+    Note the calculation of the county-to-legacy BA fractions will eventually
     be deprecated once the 134-zone structure is removed from all spatial
     inputs (see https://github.com/ReEDS-Model/ReEDS/issues/16).
-    The provided dataframe must have columns 'FIPS' and 'value'.
+
+    The provided dataframe "df" must have columns 'FIPS' and 'value'.
+    The provided dataframe "county2zone_with_legacy_bas" must have columns
+    'FIPS', 'state', 'r', and 'legacy_ba'.
     """
     required_columns = ['FIPS', 'value']
     missing_columns = [col for col in required_columns if col not in df.columns]
     if len(missing_columns) > 0:
         raise KeyError(f"Provided dataframe is missing required columns {missing_columns}")
 
-    df = (
-        df.merge(
-            county2zone.drop(columns='FIPS')
-            .rename(columns={'county': 'FIPS'})
-        )
-        .rename(columns={'ba': 'PCA_REG'})
-    )
+    df = df.merge(county2zone_with_legacy_bas)
     df['fracdata'] = (
-        df.groupby('PCA_REG')
+        df.groupby('legacy_ba')
         ['value']
         .transform(lambda x: x / x.sum())
     )
@@ -984,7 +802,7 @@ def calculate_county_fractions(df, county2zone):
 
     df = (
         df.dropna(subset='r')
-        [['PCA_REG', 'FIPS', 'fracdata', 'r', 'state', 'r_frac', 'state_frac']]
+        [['legacy_ba', 'FIPS', 'fracdata', 'r', 'state', 'r_frac', 'state_frac']]
     )
 
     return df
@@ -993,19 +811,22 @@ def write_disagg_data_files(runfiles, inputs_case):
     """
     Write files that will be used for disaggregation.
     """
-    # Get the county2zone file specific to this run (a mapping from counties
-    # to model regions) and the original county2zone file (including all
-    # counties) and combine them. The former is needed to calculate model
-    # region-to-county fractions, and the latter is needed to calculate
-    # state-to-county and BA-to-county fractions.
-    county_r_map = reeds.io.get_county2zone(os.path.dirname(inputs_case))
-    ## TEMPORARY 20260402: Use the old 134-zone county2zone until the aggregation approach is updated
-    county2zone = (
+    # Get the county2zone file for the z134 zone set and append the zones
+    # corresponding to this run. The z134 file is needed to calculate
+    # state-to-county fractions (since it includes all counties in the CONUS)
+    # and legacy BA-to-county fractions (which are needed to disaggregate
+    # inputs that are still at the z134 resolution).
+    county2zone_with_legacy_bas = (
         reeds.io.get_county2zone(GSw_ZoneSet='z134', as_map=False)
-        .rename(columns={'r':'ba'})
+        .rename(columns={'r': 'legacy_ba'})
+    )
+    county_r_map = reeds.io.get_county2zone(os.path.dirname(inputs_case))
+    county2zone_with_legacy_bas['r'] = (
+        county2zone_with_legacy_bas['FIPS'].map(county_r_map)
+    )
+    county2zone_with_legacy_bas['FIPS'] = (
+        'p' + county2zone_with_legacy_bas['FIPS']
     )
-    county2zone['county'] = 'p' + county2zone['FIPS'].astype(str).str.zfill(5)
-    county2zone['r'] = county2zone['FIPS'].map(county_r_map)
 
     filename_filepath_map = runfiles.set_index('filename')['full_filepath']
     for filename in [
@@ -1031,47 +852,18 @@ def write_disagg_data_files(runfiles, inputs_case):
     
         # Calculate state/region/BA-to-county fractions for the
         # disagg variable and write to inputs_case
-        df = calculate_county_fractions(df, county2zone)
+        df = calculate_county_fractions(df, county2zone_with_legacy_bas)
         df.to_csv(os.path.join(inputs_case, filename), index=False)
 
     return
 
-def map_and_aggregate(
-    df,
-    regions_and_agglevel,
-    region_file_entry,
-    region_col,
-    aggfunc=None
-):
-    '''
-    Maps counties to BAs and aggregates according to aggfunc if provided.
-    '''
-    merged = (
-            df.set_index(region_col)
-            .merge(regions_and_agglevel['ba_county'], left_index=True, right_on='county')
-            .drop('county', axis=1)
-            .rename(columns={'ba': region_col})
-        )
-
-    if aggfunc:
-        fix_cols = region_file_entry['fix_cols'].split(',')
-        if all([fix_col in merged.columns for fix_col in fix_cols]):
-            groupby_cols = list(set(fix_cols + [region_col]))
-            df = merged.groupby(groupby_cols, as_index=False).agg(aggfunc)
-        else:
-            df = merged.groupby(region_col, as_index=False).agg(aggfunc)
-
-
-    return df
-
 
 def write_region_indexed_file(
     df,
     dir_dst,
     source_deflator_map,
     sw,
-    region_file_entry,
-    regions_and_agglevel
+    region_file_entry
 ):
     """
     Write a single region-indexed file to the dir_dst directory
@@ -1112,15 +904,17 @@ def write_region_indexed_file(
                 # Adjust for inflation
                 df['price'] = df['price'].astype(float) * source_deflator_map[filepath]
             case 'unitdata.csv':
-                fips_ba_map = regions_and_agglevel['ba_county'].dropna().set_index('county')['ba']
-                df['reeds_ba'] = df['FIPS'].map(fips_ba_map)
+                # Map counties to zones
+                county2zone = reeds.io.get_county2zone(case=os.path.dirname(inputs_case))
+                county2zone.index = 'p' + county2zone.index
+                df['r'] = df['FIPS'].map(county2zone)
                 ## If using offshore zones, map offshore wind units from land to offshore zones
                 if int(sw.GSw_OffshoreZones):
                     df = reeds.spatial.assign_to_offshore_zones(df)
-                num_units_missing_bas = len(df.loc[df.reeds_ba.isna()])
-                if num_units_missing_bas > 0:
+                num_units_missing_zones = len(df.loc[df.r.isna()])
+                if num_units_missing_zones > 0:
                     raise ValueError(
-                        f"{num_units_missing_bas} units were not mapped to any BAs."
+                        f"{num_units_missing_zones} units were not mapped to any zones."
                     )
             case _:
                 pass
@@ -1133,7 +927,6 @@ def write_region_indexed_files(
     sw,
     region_files,
     regions_and_agglevel,
-    agglevel_variables,
     source_deflator_map
 ):
     """
@@ -1155,7 +948,6 @@ def write_region_indexed_files(
             df = subset_to_valid_regions(
                 sw,
                 region_file_entry,
-                agglevel_variables,
                 regions_and_agglevel,
                 inputs_case
             )
@@ -1164,15 +956,12 @@ def write_region_indexed_files(
                 inputs_case,
                 source_deflator_map,
                 sw,
-                region_file_entry,
-                regions_and_agglevel
+                region_file_entry
             )
 
 
 def write_miscellaneous_files(
     sw,
-    regions_and_agglevel,
-    agglevel_variables,
     inputs_case,
     reeds_path
 ):
@@ -1199,6 +988,10 @@ def write_miscellaneous_files(
                 ][0:len(sw['GSw_PVB_Types'].split('_'))]}
     ).to_csv(os.path.join(inputs_case, 'pvb_bir.csv'), index=False)
 
+    ### County-to-zone mapping
+    county2zone = reeds.io.get_county2zone(case=os.path.dirname(inputs_case))
+    county2zone.index = 'p' + county2zone.index
+
     # Constant value if input is float, otherwise named profile
     # Methane leakage rate:
     try:
@@ -1274,12 +1067,13 @@ def write_miscellaneous_files(
             reeds_path,'inputs','emission_constraints','county_co2_share_egrid_2022.csv'),
         index_col=0)
 
-    # Filter the counties that are in chosen GSw_Region
-    val_county = pd.read_csv(os.path.join(inputs_case,'county.csv'),names=['r'])
-
     # Merge emission share by county with the counties in GSw_Region and calculate emission share of GSw_Region
-    region_em_share = val_county.merge(em_share, on='r', how='left').fillna(0)
-    region_em_share = region_em_share['share'].sum()
+    region_em_share = (
+        em_share.reindex(county2zone.index)
+        .fillna(0)
+        ['share']
+        .sum()
+    )
 
     # Apply the emission share to national cap to get the emission cap trajectory of GSw_Region
     co2_cap *= region_em_share
@@ -1403,31 +1197,9 @@ def write_miscellaneous_files(
     # Add capacity deployment limits based on interconnection queue data
     cap_queue = pd.read_csv(
         os.path.join(reeds_path,'inputs','capacity_exogenous','interconnection_queues.csv'))
-    # Filter the counties that are in chosen GSw_Region
-    cap_queue = cap_queue[cap_queue['r'].isin(val_county['r'])]
-
-    # Single resolution procedure
-    if (agglevel_variables["lvl"] != 'county') and ('county' not in agglevel_variables['agglevel']):
-        cap_queue = cap_queue.rename(columns={'r':'county'})
-        cap_queue = pd.merge(cap_queue, regions_and_agglevel["r_county"], on='county', how='left').dropna()
-        cap_queue = cap_queue.drop('county', axis=1)
-
-    # Mixed resolution procedure
-    elif agglevel_variables['lvl'] == 'mult':
-        # Filter out BA regions and aggregate
-        cap_queue_ba = cap_queue[cap_queue['r'].isin(agglevel_variables['BA_county_list'])].copy()
-        if 'aggreg' in agglevel_variables['agglevel'] :
-            r_county_dict = regions_and_agglevel["r_county"].set_index('county')['r'].to_dict()
-            cap_queue_ba['r'] = cap_queue_ba['r'].map(r_county_dict)
-
-        else:
-            cap_queue_ba['r'] = cap_queue_ba['r'].map(agglevel_variables['BA_2_county'])
-
-        # Filter out county regions
-        cap_queue_county = cap_queue[cap_queue['r'].isin(agglevel_variables['county_regions'])]
-
-        #combine BA and county
-        cap_queue = pd.concat([cap_queue_ba,cap_queue_county])
+    # Map counties to zones
+    cap_queue['r'] = cap_queue['r'].map(county2zone)
+    cap_queue = cap_queue.dropna(subset='r')
 
     cap_queue = cap_queue.groupby(['tg','r'],as_index=False).sum()
     cap_queue.to_csv(os.path.join(inputs_case,'cap_limit.csv'), index=False)
@@ -1506,8 +1278,6 @@ def main(reeds_path, inputs_case):
     ### ===========================================================================
     # Obtain data necessary to filter and aggregate regions
     regions_and_agglevel = get_regions_and_agglevel(reeds_path, inputs_case)
-    # Use agglevel_variables function to obtain spatial resolution variables
-    agglevel_variables = reeds.spatial.get_agglevel_variables(reeds_path, inputs_case)
 
     #%% ===========================================================================
     ### --- Copying files ---
@@ -1515,12 +1285,7 @@ def main(reeds_path, inputs_case):
 
     sw = reeds.io.get_switches(inputs_case)
 
-    runfiles, non_region_files, region_files = read_runfiles(
-        reeds_path,
-        inputs_case,
-        sw,
-        agglevel_variables
-    )
+    runfiles, non_region_files, region_files = read_runfiles(reeds_path, sw)
 
     # Rewrite the switches tables as GAMS-readable definition
     # (gswitches.csv is first written at runreeds.py)
@@ -1540,17 +1305,9 @@ def main(reeds_path, inputs_case):
         sw,
         region_files,
         regions_and_agglevel,
-        agglevel_variables,
         source_deflator_map
     )
 
-    # Create a maps.gpkg for this run
-    # Skip if using region dis/aggregation, maps will be written in aggregation_regions.py.
-    # Run if using mixed resolution aggreg-county combination 
-    if agglevel_variables['lvl'] == 'ba' or (
-        agglevel_variables['lvl'] == 'mult' and 'aggreg' in agglevel_variables['agglevel']):
-        generate_maps_gpkg(inputs_case)
-
     #%% ===========================================================================
     ### --- Exceptions ---
     ### ===========================================================================
@@ -1558,12 +1315,13 @@ def main(reeds_path, inputs_case):
     # Needs to run after copy of non-region files
     write_miscellaneous_files(
         sw,
-        regions_and_agglevel,
-        agglevel_variables,
         inputs_case,
         reeds_path
     )
 
+    # Create a maps.gpkg for this run
+    generate_maps_gpkg(inputs_case)
+
 
 #%% Procedure
 if __name__ == '__main__' and not hasattr(sys, 'ps1'):
diff --git a/reeds/input_processing/hourly_repperiods.py b/reeds/input_processing/hourly_repperiods.py
index d45142b8..e1ceedaa 100644
--- a/reeds/input_processing/hourly_repperiods.py
+++ b/reeds/input_processing/hourly_repperiods.py
@@ -258,27 +258,15 @@ def main(
         os.path.join(inputs_case, 'val_r_all.csv'), header=None).squeeze(1).tolist()
     modelyears = pd.read_csv(
         os.path.join(inputs_case, 'modeledyears.csv')).columns.astype(int)
-    # Use agglevel_variables function to obtain spatial resolution variables 
-    agglevel_variables  = reeds.spatial.get_agglevel_variables(reeds_path, inputs_case)
 
     #%% Get map from yperiod, hour, and h_of_period to timestamp
     timestamps = reeds.timeseries.make_timestamps(sw)
     timestamps_myr = timestamps.loc[timestamps.year.isin(sw['GSw_HourlyWeatherYears'])].copy()
 
-    ### Get region hierarchy for use with GSw_HourlyClusterRegionLevel
+    ### Get region hierarchy and rmap
     hierarchy = pd.read_csv(
         os.path.join(inputs_case,'hierarchy.csv')).rename(columns={'*r':'r'}).set_index('r')
-    hierarchy_orig = pd.read_csv(
-        os.path.join(inputs_case,'hierarchy_original.csv'))
-    
-    if sw.GSw_HourlyClusterRegionLevel == 'r':
-        rmap = pd.Series(hierarchy_orig.index, index=hierarchy_orig.index)
-    elif agglevel_variables['agglevel'] == 'county' or 'county' in agglevel_variables['agglevel']:
-        rmap = hierarchy[sw['GSw_HourlyClusterRegionLevel']]
-    elif agglevel_variables['agglevel'] in ['ba','aggreg']:
-        rmap = (hierarchy_orig.loc[hierarchy_orig['ba'].isin(val_r_all)]
-                [['aggreg',sw['GSw_HourlyClusterRegionLevel']]]
-                .drop_duplicates().set_index('aggreg')).squeeze(1)
+    rmap = reeds.io.get_rmap(inputs_case, sw['GSw_HourlyClusterRegionLevel'])
 
     #%% Load supply curves to use for available capacity weighting
     sc = {
diff --git a/reeds/input_processing/hydcf.py b/reeds/input_processing/hydcf.py
index c62e3b20..aa967383 100644
--- a/reeds/input_processing/hydcf.py
+++ b/reeds/input_processing/hydcf.py
@@ -321,22 +321,16 @@ def get_hydro_plants(inputs_case: str) -> pd.DataFrame:
     Returns:
         pd.DataFrame
     """
-    # Get county-to-region mapping
-    county2zone = reeds.io.get_county2zone(os.path.dirname(inputs_case))
-    county2zone.index = 'p' + county2zone.index
     # Get plant database and filter down to hydro plants
     gendb = pd.read_csv(
         os.path.join(inputs_case, 'unitdata.csv'),
-        usecols=['T_PID', 'tech', 'FIPS']
+        usecols=['T_PID', 'tech', 'r']
     )
     hydro_plants = (
         gendb.loc[gendb.tech.str.startswith('hyd')]
         .drop_duplicates('T_PID')
         .set_index('T_PID')
     )
-    # Assign each plant to a model region and reformat
-    hydro_plants['r'] = hydro_plants['FIPS'].map(county2zone)
-    hydro_plants = hydro_plants.drop(columns='FIPS')
     hydro_plants.index = hydro_plants.index.astype(str)
 
     return hydro_plants
diff --git a/reeds/input_processing/mcs_sampler.py b/reeds/input_processing/mcs_sampler.py
index 605b2bfc..626eb624 100644
--- a/reeds/input_processing/mcs_sampler.py
+++ b/reeds/input_processing/mcs_sampler.py
@@ -166,7 +166,6 @@ def read_csv_h5_file(sw_runfiles_csv, aux_files, reeds_path, inputs_case) -> pd.
         df = copy_files.subset_to_valid_regions(
             aux_files['sw'],
             sw_runfiles_csv,
-            aux_files['agglevel_variables'],
             aux_files['regions_and_agglevel'],
             inputs_case,
             agg=False,
@@ -204,36 +203,6 @@ def read_csv_h5_file(sw_runfiles_csv, aux_files, reeds_path, inputs_case) -> pd.
 
     return df
 
-
-def get_hierarchy_file(inputs_case: str, ReEDS_resolution: str) -> pd.DataFrame:
-    """
-    The hierarchy file in `{inputs_case}/hierarchy.csv` does not contain a
-    differentiation between "ba" and "aggreg" resolution. This function
-    reconstructs the hierarchy file with all possible combinations relevant
-    to the MCS.
-
-    Args:
-        inputs_case (str): Path to the inputs case directory.
-        ReEDS_resolution (str): The spatial resolution used in ReEDS (e.g., 'ba', 'aggreg').
-
-    Returns:
-        pd.DataFrame: A DataFrame with the hierarchy information relevant to the regions
-            considered in the inputs_casse run.
-    """
-    original_hierarchy_file = pd.read_csv(
-        os.path.join(inputs_case, "hierarchy_original.csv")
-    )
-
-    valid_regions = pd.read_csv(
-        os.path.join(inputs_case, "hierarchy.csv")
-    )['*r'].values
-
-    filtered_hierarchy  = original_hierarchy_file[
-        original_hierarchy_file[ReEDS_resolution].isin(valid_regions)
-    ].reset_index(drop=True)
-
-    return filtered_hierarchy
-
 def check_lhs_param_order(lower, upper):
     """Ensure lower bounds are less than upper bounds, swapping where necessary.
 
@@ -569,20 +538,12 @@ def get_dist_instructions(reeds_path: str, inputs_case: str) -> Tuple[pd.DataFra
     df_input_dist_ex['reeds_path'] = reeds_path
     df_input_dist_ex['inputs_case'] = inputs_case
 
-    agglevel_variables = reeds.spatial.get_agglevel_variables(reeds_path, inputs_case)
     # Read runfiles.csv to get instructions on how files must be copied.
-    runfiles, nonregion_files, region_files = copy_files.read_runfiles(
-        reeds_path, inputs_case, sw, agglevel_variables)
+    runfiles, nonregion_files, region_files = copy_files.read_runfiles(reeds_path, sw)
 
-    ReEDS_resolution = sw['GSw_RegionResolution']
     # Process each distribution instruction.
     for i, input_dist_row in df_input_dist.iterrows():
 
-        # If ReEDS_resolution is aggreg but weight_r is 'ba' change it to aggreg
-        if ReEDS_resolution == 'aggreg' and input_dist_row['weight_r'] == 'ba':
-            df_input_dist_ex.at[i, 'weight_r'] = 'aggreg'
-            print(f"[Warning]: The weight_r for {input_dist_row['name']} was changed to 'aggreg'")
-
         # Iterate over each switch in the instruction.
         for sw_i, assignments_list in enumerate(input_dist_row['assignments_list']):
 
@@ -613,7 +574,7 @@ def get_dist_instructions(reeds_path: str, inputs_case: str) -> Tuple[pd.DataFra
 
     source_deflator_map = copy_files.get_source_deflator_map(reeds_path)
 
-    hierarchy_file = get_hierarchy_file(inputs_case, sw['GSw_RegionResolution'])
+    hierarchy_file = reeds.io.get_hierarchy(inputs_case).reset_index()
 
     # Save the auxiliary info in a dictionary.
     aux_files = {
@@ -622,7 +583,6 @@ def get_dist_instructions(reeds_path: str, inputs_case: str) -> Tuple[pd.DataFra
         'region_files': region_files,
         'source_deflator_map': source_deflator_map,
         'regions_and_agglevel': regions_and_agglevel,
-        'agglevel_variables': agglevel_variables,
         'hierarchy_file': hierarchy_file,
     }
 
@@ -679,7 +639,8 @@ def get_all_region_weights(
     Args:
         distribution (str): The distribution to use for sampling.
         dist_params (list): The parameters for the distribution.
-        hierarchy_file (pd.DataFrame): DataFrame with the hierarchy information from get_hierarchy_file (.)
+        hierarchy_file (pd.DataFrame): DataFrame with the hierarchy information from
+            reeds.io.get_hierarchy()
         sample_hierarchy_lvl (str): The hierarchy level which will be assigned unique weights.
 
     Returns:
@@ -696,7 +657,7 @@ def get_all_region_weights(
         r_weights = get_region_weights(distribution, dist_params)
 
         # Retrieve all BAs linked to the current region
-        bas = hierarchy_file.loc[hierarchy_file[sample_hierarchy_lvl] == region, "ba"].values
+        bas = hierarchy_file.loc[hierarchy_file[sample_hierarchy_lvl] == region, "r"].values
 
         # Assign weights to each BA, cendiv, and aggreg
         for ba in bas:
@@ -741,15 +702,6 @@ def __init__(
         # Get all general region weights
         self.r_weights = get_all_region_weights(
             self.distribution, self.dist_params, self.hierarchy_file, self.sample_hierarchy_lvl)
-        ## Include aggregated region weights
-        if aux_files['sw']['GSw_RegionResolution'] == 'aggreg':
-            self.r_weights = {
-                **self.r_weights,
-                **{
-                    aux_files['hierarchy_file'].set_index('ba').aggreg.get(k,k): v
-                    for k,v in self.r_weights.items()
-                },
-            }
 
         # Store the weights for the recf files (CF files)
         # Those are computed during the the supply curve file sampling 
@@ -1145,14 +1097,10 @@ def __init__(self, sample_group, aux_files, n_samples, mcs_run_number, lhs_sampl
         self.inputs_case = sample_group['inputs_case']
         self.distribution = sample_group['dist']
         self.dist_params = sample_group['dist_params']
-        self.ReEDS_resolution = aux_files['sw']['GSw_RegionResolution']
-        if self.ReEDS_resolution=='aggreg' and sample_group['weight_r']=='ba':
-            self.sample_hierarchy_lvl = 'aggreg'
-        else:
-            self.sample_hierarchy_lvl = sample_group['weight_r']
+        self.sample_hierarchy_lvl = sample_group['weight_r']
 
         # Inputs that require special treatment
-        self.hierarchy_file = get_hierarchy_file(self.inputs_case, self.ReEDS_resolution)
+        self.hierarchy_file = reeds.io.get_hierarchy(self.inputs_case).reset_index()
 
         # Store the samples for each switch (a single sw may have multiple files that is
         # why we refer to the switch by its adjusted name)
@@ -1829,8 +1777,7 @@ def write_samples(
             # Get the row of the region-indexed file
             region_files_row = aux_files['region_files'].query('filename == @file_name').iloc[0]
             copy_files.write_region_indexed_file(sample_values, dir_dst, aux_files['source_deflator_map'],
-                                                    aux_files['sw'], region_files_row,
-                                                    aux_files['regions_and_agglevel'])
+                                                    aux_files['sw'], region_files_row)
         # ...if we have a csv file that isn't region-indexed (including switches.csv)
         elif file_termination == '.csv':
             if file_name == 'switches.csv':
diff --git a/reeds/input_processing/outage_rates.py b/reeds/input_processing/outage_rates.py
index 7ccadf22..5d2a6dac 100644
--- a/reeds/input_processing/outage_rates.py
+++ b/reeds/input_processing/outage_rates.py
@@ -218,10 +218,7 @@ def calc_outage_forced(
     ### Derived inputs
     sw = reeds.io.get_switches(inputs_case)
     hierarchy = reeds.io.get_hierarchy(reeds.io.standardize_case(inputs_case))
-    val_ba = (
-        pd.read_csv(os.path.join(inputs_case, 'val_ba.csv'), header=None)
-        .squeeze(1).values
-    )
+    val_r = reeds.io.read_input(inputs_case, 'r').squeeze(1).values
     ## Static forced outage rates (for filling empties)
     outage_forced_static = pd.read_csv(
         os.path.join(inputs_case, 'outage_forced_static.csv'),
@@ -243,7 +240,7 @@ def calc_outage_forced(
     if sw.GSw_OutageScen.lower() == 'static':
         ### Fill static data for all techs and modeled regions
         df = pd.concat(
-            {r: outage_forced_static for r in val_ba},
+            {r: outage_forced_static for r in val_r},
             axis=0,
             names=('r','i'),
         ).reorder_levels(['i','r']).sort_index()
diff --git a/reeds/input_processing/recf.py b/reeds/input_processing/recf.py
index 40204f8d..0f5d6c13 100644
--- a/reeds/input_processing/recf.py
+++ b/reeds/input_processing/recf.py
@@ -520,8 +520,23 @@ def main(reeds_path, inputs_case):
     cspcf = cspcf.rename(columns=dict(zip(cspcf.columns, [f'csp_{i}' for i in cspcf.columns])))
     reeds.io.write_profile_to_h5(cspcf.astype(np.float32), 'csp.h5', inputs_case)
     ### Overwrite the original hierarchy.csv based on capcredit_hierarchy_level
-    hierarchy.rename_axis('*r').to_csv(
-        os.path.join(inputs_case, 'hierarchy.csv'), index=True, header=True)
+    (
+        hierarchy.rename_axis('*r')
+        [[
+            'nercr',
+            'transreg',
+            'transgrp',
+            'cendiv',
+            'st',
+            'interconnect',
+            'country',
+            'usda_region',
+            'h2ptcreg',
+            'hurdlereg',
+            'ccreg'
+        ]]
+        .to_csv(os.path.join(inputs_case, 'hierarchy.csv'), index=True, header=True)
+    )
     ccreg = pd.Series(hierarchy.ccreg.unique())
     reeds.io.write_to_inputs_h5(
         ccreg, 'ccreg', inputs_case, gamstype='set', comment='capacity credit region',
diff --git a/reeds/input_processing/runfiles.csv b/reeds/input_processing/runfiles.csv
index 6ca5b199..bfd30029 100644
--- a/reeds/input_processing/runfiles.csv
+++ b/reeds/input_processing/runfiles.csv
@@ -142,7 +142,6 @@ minCF.csv,inputs/plant_characteristics/minCF.csv,int(sw.GSw_MinCF) != 0,ignore,i
 min_retire_age.csv,inputs/plant_characteristics/min_retire_age.csv,1,ignore,ignore,,,,,0,,,,,,
 mingen_fixed.csv,inputs/plant_characteristics/mingen_fixed.csv,int(sw.GSw_MingenFixed) != 0,ignore,ignore,,,*i,,0,,,,,,
 minloadfrac0.csv,inputs/plant_characteristics/minloadfrac0.csv,(int(sw.GSw_Mingen) != 0) or (int(sw.GSw_MinLoading) != 0),ignore,ignore,,,,,0,,,,,,
-modeled_regions.csv,inputs/userinput/modeled_regions.csv,1,ignore,ignore,,,,,,,,,,,
 month2quarter.csv,inputs/temporal/month2quarter.csv,1,ignore,ignore,,,,,0,,,,,,
 mttr.csv,inputs/plant_characteristics/mttr.csv,1,ignore,ignore,,,tech,,0,,,,,,
 natgas_price_cendiv.csv,inputs/fuelprices/ng_{ngscen}.csv,1,ignore,ignore,wide_cendiv,year,,1,0,,,,,,
diff --git a/reeds/input_processing/transmission.py b/reeds/input_processing/transmission.py
index 02d4d9e3..7de08db3 100644
--- a/reeds/input_processing/transmission.py
+++ b/reeds/input_processing/transmission.py
@@ -358,8 +358,11 @@ def get_trancap_init(case, interface_params, level='r'):
         & dfout['rr'].isin(valid_regions[level])
     ].copy()
 
-    ### TEMPORARY 20260402: Drop county interfaces with no distance/cost
-    if (level == 'r') and (sw.GSw_RegionResolution in ['county', 'mixed']):
+    ### Drop county interfaces with no distance/cost if applicable
+    drop_interfaces = sw.GSw_ZoneSet in reeds.inputs.get_applicable_zonesets(
+        'drop_interfaces_missing_cost'
+    )
+    if (level == 'r') and drop_interfaces:
         transmission_line_fom = get_transmission_fom(case, interface_params)
         indices = ['r', 'rr', 'trtype']
         drop = (
diff --git a/reeds/input_processing/writecapdat.py b/reeds/input_processing/writecapdat.py
index fd49d594..0e3d3b4b 100644
--- a/reeds/input_processing/writecapdat.py
+++ b/reeds/input_processing/writecapdat.py
@@ -120,7 +120,7 @@ def create_rsc_wsc(gendb,TECH,scalars,startyear):
 ### --- MAIN FUNCTION ---
 ### ===========================================================================
 
-def main(reeds_path, inputs_case, agglevel, regions):
+def main(reeds_path, inputs_case):
     
     # #%% Settings for testing
     #reeds_path = "/Users/apham/Documents/GitHub/ReEDS/ReEDS/"
@@ -150,6 +150,8 @@ def main(reeds_path, inputs_case, agglevel, regions):
         os.path.join(inputs_case,'modeledyears.csv')
     ).columns.astype(int).values.tolist()
 
+    regions = reeds.io.read_input(inputs_case, 'r').squeeze(1).values
+
     ####################
     ### DICTIONARIES ###
 
@@ -217,20 +219,6 @@ def main(reeds_path, inputs_case, agglevel, regions):
     print('Importing generator database:')
     gdb_use = pd.read_csv(os.path.join(inputs_case,'unitdata.csv'), low_memory=False)
 
-    
-    rcol_dict = {'county':'FIPS', 'ba':'reeds_ba'}
-    # Create the 'r_col' column
-    if agglevel in ['county','ba']:
-        r_col = rcol_dict[agglevel]        
-        gdb_use['r'] = gdb_use[r_col].copy()
-        # Filter generator database to regions that match the spatial resolution of the run
-        gdb_use = gdb_use[gdb_use['r'].isin(regions)]
-    elif agglevel == 'aggreg':
-        rb_aggreg = pd.read_csv(os.path.join(inputs_case,'rb_aggreg.csv'), index_col='ba').squeeze(1)
-        gdb_use = gdb_use.assign(r=gdb_use.reeds_ba.map(rb_aggreg))
-        # Filter generator database to regions that match the spatial resolution of the run
-        gdb_use = gdb_use[gdb_use['r'].isin(regions)]
-
     # If PVB is turned off, consider all PVB as UPV and battery_li for existing and prescribed builds 
     # If PVB is turned on, consider all PVB as 'pvb'
     if GSw_PVB == 0:
@@ -830,62 +818,7 @@ def main(reeds_path, inputs_case, agglevel, regions):
     )
     print('Starting writecapdat.py')
 
-
-    # Use agglevel_variables function to obtain spatial resolution variables 
-    agglevel_variables  = reeds.spatial.get_agglevel_variables(reeds_path, inputs_case)
-
-    # For mixed resolution runs the main function of writecapdat needs to be executed separately for each desired resolution 
-    # Then the data from each resolution are combined and written to the inputs_case folder 
-    comments = {}
-    if agglevel_variables['lvl'] == 'mult':
-        for resolution in agglevel_variables['agglevel']:
-            if resolution == 'aggreg':
-                aggreg_data, _comments = main(
-                    reeds_path, inputs_case, agglevel=resolution, 
-                    regions=agglevel_variables['ba_regions'],
-                )
-                comments = {**comments, **_comments}
-            if resolution == 'ba':
-                ba_data, _comments = main(
-                    reeds_path, inputs_case, agglevel=resolution, 
-                    regions=agglevel_variables['ba_regions'],
-                )
-                comments = {**comments, **_comments}
-            if resolution == 'county':
-                county_data, _comments = main(
-                    reeds_path, inputs_case, agglevel=resolution,
-                    regions=agglevel_variables['county_regions'],
-                )
-                comments = {**comments, **_comments}
-        
-        # Combine and write mixed resolution data
-        # ReEDS only supports county-BA, county-aggreg combinations 
-        combined_data = {}
-        if 'ba' in agglevel_variables['agglevel']:
-            for key in ba_data.keys() :
-                if county_data[key].empty:
-                    combined_data[key] = ba_data[key]
-                elif ba_data[key].empty:
-                    combined_data[key] = county_data[key]
-                else:
-                    combined_data[key] = pd.concat([ba_data[key], county_data[key]])
-
-        if 'aggreg' in agglevel_variables['agglevel']:
-            for key in aggreg_data.keys() :
-                if county_data[key].empty:
-                    combined_data[key] = aggreg_data[key]
-                elif aggreg_data[key].empty:
-                    combined_data[key] = county_data[key]
-                else:
-                    combined_data[key] = pd.concat([aggreg_data[key], county_data[key]])
-        
-        data = combined_data
-
-    # Single Resolution Procedure
-    else: 
-        agglevel = agglevel_variables['agglevel']
-        regions = reeds.io.read_input(inputs_case, agglevel).squeeze(1).values
-        data, comments = main(reeds_path, inputs_case,agglevel, regions)
+    data, comments = main(reeds_path, inputs_case)
 
     # Write it
     print('Writing out capacity data')
diff --git a/reeds/input_processing/writesupplycurves.py b/reeds/input_processing/writesupplycurves.py
index 610d6fbc..449b08b8 100644
--- a/reeds/input_processing/writesupplycurves.py
+++ b/reeds/input_processing/writesupplycurves.py
@@ -71,14 +71,10 @@ def agg_supplycurve(
     scpath,
     inputs_case,
     numbins_tech,
-    agglevel,
     bin_method='equal_cap_cut',
     bin_col='supply_curve_cost_per_mw',
-    spur_cutoff=1e7, 
-    agglevel_variables=None,
+    spur_cutoff=1e7,
     deflate=None,
-    sw=None,
-    write=False,
 ):
     """
     """
@@ -142,8 +138,6 @@ def main(
     ### Overwrite switches with keyword arguments
     for kw, arg in kwargs.items():
         sw[kw] = arg
-    endyear = int(sw.endyear)
-    startyear = int(sw.startyear)
     geohydrosupplycurve = sw.geohydrosupplycurve
     egssupplycurve = sw.egssupplycurve
     egsnearfieldsupplycurve = sw.egsnearfieldsupplycurve
@@ -157,10 +151,6 @@ def main(
         "egs": int(sw.numbins_egs_allkm),
     }
 
-    # Use agglevel_variables function to obtain spatial resolution variables 
-    agglevel_variables  = reeds.spatial.get_agglevel_variables(reeds_path, inputs_case)
-    agglevel = agglevel_variables['agglevel']
-
     val_r_all = pd.read_csv(
         os.path.join(inputs_case,'val_r_all.csv'), header=None).squeeze(1).tolist()
     # Read in tech-subset-table.csv to determine number of csp configurations
@@ -222,12 +212,11 @@ def main(
     for s in wind_types:
         windin[s], wind[s] = agg_supplycurve(
             scpath=os.path.join(inputs_case,f'supplycurve_wind-{s}.csv'),
-            inputs_case=inputs_case, 
-            agglevel=agglevel,
-            numbins_tech=numbins[f'wind-{s}'], spur_cutoff=spur_cutoff,
-            agglevel_variables=agglevel_variables, deflate=deflate,
-            sw=sw, write=write
-            )
+            inputs_case=inputs_case,
+            numbins_tech=numbins[f'wind-{s}'],
+            spur_cutoff=spur_cutoff,
+            deflate=deflate,
+        )
         
         cost_components = (
             wind[s][["cost_total_trans_usd_per_mw", "capital_adder_per_mw"]]
@@ -320,11 +309,10 @@ def main(
     upvin, upv = agg_supplycurve(
         scpath=os.path.join(inputs_case, 'supplycurve_upv.csv'),
         inputs_case=inputs_case,
-        agglevel=agglevel,
-        numbins_tech=numbins['upv'], spur_cutoff=spur_cutoff,
-        agglevel_variables=agglevel_variables, deflate=deflate,
-        sw=sw, write=write
-        )
+        numbins_tech=numbins['upv'],
+        spur_cutoff=spur_cutoff,
+        deflate=deflate,
+    )
 
     # Similar to wind, save the trans vs cap components and then concatenate them below just
     # before outputting rsc_combined.csv
@@ -398,13 +386,12 @@ def main(
     ###################
 
     if int(sw["GSw_CSP"]):
-        cspin, csp = agg_supplycurve(
+        _, csp = agg_supplycurve(
             scpath=os.path.join(inputs_case, 'supplycurve_csp.csv'),
             inputs_case=inputs_case,
-            agglevel=agglevel,
-            numbins_tech=numbins['csp'], spur_cutoff=spur_cutoff,
-            agglevel_variables=agglevel_variables, deflate=deflate,
-            sw=sw, write=False
+            numbins_tech=numbins['csp'],
+            spur_cutoff=spur_cutoff,
+            deflate=deflate,
         )
 
         ### Normalize formatting
@@ -480,11 +467,12 @@ def main(
             geoin[s], geo[s] = agg_supplycurve(
                 scpath=os.path.join(
                     inputs_case,
-                    f'supplycurve_{s}.csv'),
-                numbins_tech=numbins[s], inputs_case=inputs_case,
-                agglevel=agglevel,
-                spur_cutoff=spur_cutoff,agglevel_variables=agglevel_variables, deflate=deflate,
-                sw=sw, write=False
+                    f'supplycurve_{s}.csv'
+                ),
+                numbins_tech=numbins[s],
+                inputs_case=inputs_case,
+                spur_cutoff=spur_cutoff,
+                deflate=deflate
             )
             spurout_list.append(
                 geo[s]
diff --git a/reeds/inputs.py b/reeds/inputs.py
index e598dc26..29bd8023 100644
--- a/reeds/inputs.py
+++ b/reeds/inputs.py
@@ -106,22 +106,7 @@ def add_intermediate_switches(dfcases:pd.DataFrame) -> pd.DataFrame:
     for case in cases:
         sw = dfcases[case]
         new_switches[case] = {}
-        ### TEMPORARY 20260402: The GSw_RegionResolution switch is deprecated;
-        ### for now, hardcode its value for the region resolutions that use it
-        match sw['GSw_ZoneSet']:
-            case 'z134':
-                GSw_RegionResolution = 'ba'
-            case 'z3109':
-                GSw_RegionResolution = 'county'
-            case 'PJMcounty' | 'UTcounty':
-                GSw_RegionResolution = 'mixed'
-            case _:
-                GSw_RegionResolution = 'aggreg'
-        new_switches[case]['GSw_RegionResolution'] = GSw_RegionResolution
         ### TEMPORARY 20260402: Turn off itlgrp constraint until it's fixed
-        # new_switches[case]['GSw_itlgrpConstraint'] = str(int(
-        #     sw['GSw_RegionResolution'] in ['county', 'mixed']
-        # ))
         new_switches[case]['GSw_itlgrpConstraint'] = '0'
         ## 'meshed' offshore files are only used when offshore zones are turned on
         new_switches[case]['GSw_OffshoreFiles'] = (
@@ -789,25 +774,25 @@ def get_b2b(case=None, **kwargs) -> pd.DataFrame:
     return b2b
 
 
-def check_aggreg_unique(hierarchy):
+def get_zoneset_config() -> dict:
+    configpath = Path(reeds.io.reeds_path, 'inputs', 'zones', 'zoneset_config.yaml')
+    with open(configpath, 'r') as f:
+        config = yaml.safe_load(f)
+    return config
+
+
+def get_applicable_zonesets(setting: str) -> list[str]:
     """
-    Make sure each aggreg is only assigned to a single transreg / transgrp / st / etc.
+    Get the list of zonesets that a setting should apply to. The provided
+    setting should be a field in 'inputs/zones/zoneset_config.yaml'.
     """
-    testcols = [i for i in hierarchy.columns if i != 'aggreg']
-    aggreg_errors = {}
-    for col in testcols:
-        unique_aggregs = (
-            hierarchy[[col,'aggreg']]
-            .drop_duplicates()
-            .groupby('aggreg')[col].count()
+    zoneset_config = get_zoneset_config()
+    if setting not in zoneset_config:
+        raise NotImplementedError(
+            f"The provided setting '{setting}' is invalid. "
+            "Update inputs/zones/zoneset_config.yaml to include it."
         )
-        duplicated = unique_aggregs.loc[unique_aggregs>1]
-        if len(duplicated):
-            aggreg_errors[col] = hierarchy.loc[
-                hierarchy.aggreg.isin(duplicated.index),
-                [col,'aggreg']
-            ]
-    return aggreg_errors
+    return zoneset_config[setting]
 
 
 def validate_zoneset(GSw_ZoneSet):
@@ -896,19 +881,3 @@ def validate_zoneset(GSw_ZoneSet):
         hierarchypath = Path(zonepath, 'hierarchy.csv')
         err = f'The following columns are missing from {hierarchypath}: ' + ' '.join(missing)
         raise KeyError(err)
-    ## TEMPORARY 20260402: Is each aggreg only assigned to a single hierarchy level?
-    fpath_134 = Path(zonepath, 'hierarchy_from134.csv')
-    if fpath_134.is_file():
-        hierarchy_134 = pd.read_csv(fpath_134, index_col='ba')
-        errors = check_aggreg_unique(hierarchy_134)
-        if len(errors):
-            for v in errors.values():
-                print(v)
-                print()
-            err = (
-                "There are aggreg values spanning multiple hierarchy levels for:\n > "
-                + '\n > '.join(errors.keys())
-                + f"\nPlease modify {fpath_134}\n"
-                "to ensure each aggreg is only assigned to a single hierarchy level."
-            )
-            raise ValueError(err)
diff --git a/reeds/io.py b/reeds/io.py
index 4c13b521..0aa9f1ad 100644
--- a/reeds/io.py
+++ b/reeds/io.py
@@ -127,15 +127,9 @@ def get_hierarchy(case=None, original=False, **kwargs):
             filepath = Path(standardize_case(case), 'inputs_case', 'hierarchy_original.csv')
         else:
             filepath = Path(standardize_case(case), 'inputs_case', 'hierarchy.csv')
+        hierarchy = pd.read_csv(filepath).rename(columns={'*r':'r', 'ba':'r'}).set_index('r')
     else:
-        ## TEMPORARY 20260402: Use deprecated hierarchy inputs.
-        ## Use the line below once we make the switch:
-        # hierarchy = assemble_hierarchy(case=case, **kwargs).set_index('r')
-        sw = reeds.io.get_switches(**kwargs)
-        filepath = Path(
-            reeds.io.reeds_path, 'inputs', 'zones', sw.GSw_ZoneSet, 'hierarchy_from134.csv',
-        )
-    hierarchy = pd.read_csv(filepath).rename(columns={'*r':'r', 'ba':'r'}).set_index('r')
+        hierarchy = assemble_hierarchy(case=case, **kwargs).set_index('r')
     return hierarchy
 
 
@@ -178,14 +172,43 @@ def get_county2zone(
 
     if as_map:
         dfout = dfin.set_index('FIPS')['r']
-    else:
+    elif case is None:
         fpath_countystate = Path(reeds.io.reeds_path, 'inputs', 'zones', 'county_state.csv')
         county_state = pd.read_csv(fpath_countystate, dtype=str)
         dfout = dfin.merge(county_state, on='FIPS', how='left')
+    else:
+        dfout = dfin
 
     return dfout
 
 
+def get_county_zones(
+    case: str | Path | None = None,
+    **kwargs
+) -> list[str]:
+    """
+    Get the set of county-level zones corresponding to a given zone set.
+    Reads from the inputs_case folder if {case} is provided or from the
+    default set of inputs (with key word arguments overriding case
+    switches, e.g., "GSw_ZoneSet") otherwise.
+
+    Args:
+        case: Path to a ReEDS case.
+
+    Returns:
+        list[str]
+    """
+    county2zone = get_county2zone(case, as_map=True, **kwargs)
+    county_zones = county2zone.loc[
+        county2zone.isin(
+            county2zone.value_counts()
+            .loc[county2zone.value_counts() == 1]
+            .index
+        )
+    ].tolist()
+
+    return county_zones
+
 
 def get_zone_nodes(case=None, crs='ESRI:102008', **kwargs):
     """Get the transmission node for each model zone"""
@@ -302,7 +325,10 @@ def get_dfmap(case=None, levels=None, exclude_water_areas=True):
     """Get dictionary of maps at different hierarchy levels"""
     hierarchy = (
         get_hierarchy(case, original=True)
-        .drop(columns=['aggreg', 'st_interconnect'], errors='ignore')
+        .drop(
+            columns=['aggreg', 'st_interconnect', 'md5', 'node_lat', 'node_lon'],
+            errors='ignore'
+        )
     )
     hierarchy_levels = list(hierarchy.columns)
     if levels:
@@ -1508,15 +1534,10 @@ def assemble_supplycurve(
         else:
             dfout['ba'] = dfout['region'].copy()
 
-    ## Drop reinforcement cost for counties
-    if case is not None:
-        agglevel_variables = reeds.spatial.get_agglevel_variables(
-            reeds_path, os.path.join(case, 'inputs_case')
-        )
-        counties = agglevel_variables['county_regions']
-    else:
-        counties = []
-    if len(counties):
+    if sw.GSw_ZoneSet in reeds.inputs.get_applicable_zonesets(
+        'drop_single_county_reinforcement_cost'
+    ):
+        counties = get_county_zones(GSw_ZoneSet=sw.GSw_ZoneSet)
         zerocols = ['cost_reinforcement_usd_per_mw', 'dist_reinforcement_km']
         dfout.loc[dfout.region.isin(counties), zerocols] = 0
         dfout.loc[dfout.region.isin(counties), 'cost_total_trans_usd_per_mw'] = dfout.loc[
diff --git a/reeds/reedsplots.py b/reeds/reedsplots.py
index 45c58518..99764d4e 100644
--- a/reeds/reedsplots.py
+++ b/reeds/reedsplots.py
@@ -1718,13 +1718,12 @@ def plot_prmtrade(
     val_r = reeds.io.read_input(case, 'r').squeeze(1).tolist()
     dfba = dfba.loc[val_r].copy()
 
-    if sw.get('GSw_RegionResolution', 'ba') != 'county':
-        endpoints = reeds.plots.df2gdf(
-            reeds.io.assemble_hierarchy(case).set_index('r'),
-            lat='node_lat', lon='node_lon',
-        )
-        dfba['x'] = dfba.index.map(endpoints.centroid.x)
-        dfba['y'] = dfba.index.map(endpoints.centroid.y)
+    endpoints = reeds.plots.df2gdf(
+        reeds.io.assemble_hierarchy(case).set_index('r'),
+        lat='node_lat', lon='node_lon',
+    )
+    dfba['x'] = dfba.index.map(endpoints.centroid.x)
+    dfba['y'] = dfba.index.map(endpoints.centroid.y)
 
     ### Get scaling and layout
     _vmax = dfplot.MW.abs().max() if vmax in [None, 0, 0.] else vmax
@@ -5773,15 +5772,9 @@ def plot_capacity_offline(
     ### Get temperatures
     temperatures = reeds.io.get_temperatures(case)
 
-    ## Aggregate if necessary
+    ### Get switches
     sw = reeds.io.get_switches(case)
 
-    if sw['GSw_RegionResolution'] == 'aggreg':
-        r2aggreg = pd.read_csv(
-            os.path.join(case, 'inputs_case', 'hierarchy_original.csv')
-        ).rename(columns={'ba':'r'}).set_index('r').aggreg
-        temperatures = temperatures.rename(columns=r2aggreg)
-
     hierarchy = reeds.io.get_hierarchy(case)
     r2level = hierarchy[level]
 
diff --git a/reeds/resource_adequacy/prep_data.py b/reeds/resource_adequacy/prep_data.py
index c27637ad..2579f441 100644
--- a/reeds/resource_adequacy/prep_data.py
+++ b/reeds/resource_adequacy/prep_data.py
@@ -510,11 +510,13 @@ def intify(v):
     ).round().astype(int).rename_axis('r').rename('mw')
     ## Turn off for counties by setting to zero (zeros in this file mean the max unit
     ## size is not enforced for that region in ReEDS2PRAS)
-    agglevel_variables = reeds.spatial.get_agglevel_variables(
-        reeds.io.reeds_path, os.path.join(casedir, 'inputs_case')
+    counties = reeds.io.get_county_zones(casedir)
+    unconstrain_counties = sw.GSw_ZoneSet in (
+        reeds.inputs.get_applicable_zonesets(
+            'reeds2pras_unitsize_unconstrain_counties'
+        )
     )
-    counties = agglevel_variables['county_regions']
-    if len(counties):
+    if len(counties) and unconstrain_counties:
         csvout['max_unitsize'].loc[counties] = 0
 
     #%% Strip water tech suffixes from water-dependent technologies
diff --git a/reeds/resource_adequacy/reeds2pras/src/utils/reeds_data_parsing.jl b/reeds/resource_adequacy/reeds2pras/src/utils/reeds_data_parsing.jl
index 23597d12..47d596dd 100644
--- a/reeds/resource_adequacy/reeds2pras/src/utils/reeds_data_parsing.jl
+++ b/reeds/resource_adequacy/reeds2pras/src/utils/reeds_data_parsing.jl
@@ -876,7 +876,7 @@ function disagg_existing_capacity(
     tech_ba_year_existing = DataFrames.subset(
         unitdata,
         :tech => DataFrames.ByRow(==(tech)),
-        :reeds_ba => DataFrames.ByRow(==(pca)),
+        :r => DataFrames.ByRow(==(pca)),
         :RetireYear => DataFrames.ByRow(>(year)),
         :StartYear => DataFrames.ByRow(<=(year)),
     )
diff --git a/reeds/results.py b/reeds/results.py
index a475cfe5..5b9a0d91 100644
--- a/reeds/results.py
+++ b/reeds/results.py
@@ -583,25 +583,15 @@ def calc_reinforcement_spur_capacity_miles(case):
         .sort_values(by=['r', 'trtype', 'year'])
     )
 
-    if sw['GSw_RegionResolution'] in ['county', 'mixed']:
-        """
-        Due to some old ReEDS outputs runs we need to zero out 
-        the reinforcement line for county level regions 
-        (This can be removed in the future if countly level
-        supply curves get reinforcement distance zeroed out)
-        """
-        # Get county level regions
-        county_regions = pd.read_csv(
-            os.path.join(inputs_case, 'county2zone.csv'),
-            dtype={'FIPS':str},
-        )
-
-        county_regions['county'] = 'p' + county_regions.FIPS
-
-        # Set reinforcement distance to zero for county level regions  
+    sw = reeds.io.get_switches(case)
+    if sw.GSw_ZoneSet in reeds.inputs.get_applicable_zonesets(
+        'drop_single_county_reinforcement_cost'
+    ):
+        # Set reinforcement distance to zero for county level regions
+        county_regions = reeds.io.get_county_zones(case)
         tech_trans_out = tech_trans_out.loc[  
             ~(  
-                tech_trans_out.r.isin(county_regions['county'])  
+                tech_trans_out.r.isin(county_regions)
                 & (tech_trans_out.trtype == 'reinforcement')  
             )  
         ]    
@@ -653,8 +643,9 @@ def calc_transmission_capacity(case,levels):
 
     # pull intra and interregional transmission data into dictionaries for processing
     dict_inter = {}
-    level_map = get_level_map(case)
+    level_map = get_level_map()
     hierarchy = reeds.io.get_hierarchy(case)
+    hierarchy['r'] = hierarchy.index
     for level in levels:
         
         # Translate the level to a cleaner spatial resolution for publishing csvs. Ex. st --> State, transgrp --> Transmission Planning Subregion.
@@ -711,15 +702,11 @@ def calc_transmission_capacity(case,levels):
     
     return intraregional, interregional
 
-def get_level_map(case):
+def get_level_map():
     # for all regions available in ReEDS/inputs/hierarchy.csv, map them to a clean display name
     level_map = pd.read_csv(
         os.path.join(reeds_path, 'postprocessing', 'plots', 'level_map.csv'), 
         index_col='raw').squeeze(1)
-    
-    # add a value to level map for 'r' based on the spatial resolution of the run
-    sw = reeds.io.get_switches(case)
-    level_map['r'] = level_map.get(sw.GSw_RegionResolution)
       
     return level_map
 
diff --git a/reeds/spatial.py b/reeds/spatial.py
index cbaa0a9b..cb256289 100644
--- a/reeds/spatial.py
+++ b/reeds/spatial.py
@@ -8,128 +8,6 @@
 import reeds
 
 
-def get_agglevel_variables(reeds_path, inputs_case):
-    '''
-    This function produces a dictionary with an assortment of variables that are necessary for
-    mixed resolution runs.
-
-    ReEDS supports multiple agglevels
-    The 'lvl' variable is set to 'mult' for instances where county is included as a desired resolution.
-    This ensures that both BA and county data are copied to the inputs_case folder
-    The 'lvl' variable also ensures that BA and larger spatial aggregations use BA data and procedure
-
-    ###### variables output by function:   #######
-    lvl - indicator if one of the desired resolutions in a mixed resolution run is county or not
-    agglevel - single or multiple values to indicate resolution(s)
-    ba_regions - list of regions in a mixed resolution run that use BA resolution data
-    county_regions - list of regions in a mixed resolution run that use county resolution data
-    county_regions2ba - map county resolution regions to their BA
-    BA_county_list - list of counties that belong to regions being solved at BA
-    BA_2_county - map counties that belong to BA resolution regions back to their BA
-    ba_transgrp - list of transgroups associated with regions being solved at ba resolution
-    county_transgrp - list of transgroups associated with regions being solved at ba resolution
-
-    '''
-
-    agglevel = pd.read_csv(os.path.join(inputs_case, 'agglevels.csv'))
-
-    if len(agglevel) > 1:
-        agglevel = agglevel.squeeze().tolist()
-    else:
-        agglevel = agglevel.squeeze().split()
-
-    # Compile lists of regions in the run to be considered at ba level
-    hierarchy = pd.read_csv(
-        os.path.join(inputs_case, 'hierarchy_with_res.csv'), usecols=['*r', 'resolution']
-    )
-    hierarchy_org = pd.read_csv(os.path.join(inputs_case, 'hierarchy_original.csv'))
-    rb_aggreg = pd.read_csv(os.path.join(inputs_case, 'rb_aggreg.csv'))
-    ba_regions = hierarchy[hierarchy['resolution'] == 'ba']['*r'].to_list()
-    aggreg_regions = hierarchy[hierarchy['resolution'] == 'aggreg']['*r'].to_list()
-    aggreg_regions2ba = hierarchy_org[hierarchy_org['aggreg'].isin(aggreg_regions)]['ba'].to_list()
-    ba_regions = list(set(ba_regions + aggreg_regions + aggreg_regions2ba))
-    transgrp_regions_ba = list(set(hierarchy_org[hierarchy_org['ba'].isin(ba_regions)]['transgrp']))
-
-    ### Procedure for handling mixed-resolution ReEDS runs
-    if len(agglevel) > 1:
-        if 'county' in agglevel:
-            lvl = 'mult'
-        else:
-            lvl = 'ba'
-
-        # Create dictionaries which map county resolution regions to their BAs and which map
-        # the counties of BA resolution regions to their BA
-        # These lists/dictionaries are necessary to filter county and BA resolution data correctly
-
-        if 'county' in agglevel:
-            county_regions = hierarchy[hierarchy['resolution'] == 'county']['*r'].to_list()
-            r_ba = pd.read_csv(os.path.join(inputs_case, 'r_ba.csv'))
-            r_ba_dict = r_ba.set_index('r')['ba'].to_dict()
-            # List of BAs associated with county resolution regions
-            county_regions2ba = pd.DataFrame(county_regions)[0].map(r_ba_dict).unique().tolist()
-            # Need list of transgrps associated with regions being solved at county resolution
-            transgrp_regions_county = list(
-                set(hierarchy_org[hierarchy_org['ba'].isin(county_regions2ba)]['transgrp'])
-            )
-            # Need county2zone
-            ## TEMPORARY 20260402
-            county2zone = reeds.io.get_county2zone(GSw_ZoneSet='z134', as_map=False)
-            # Need to create mapping between aggreg and county
-            if 'aggreg' in agglevel:
-                county2zone = county2zone[county2zone['r'].isin(rb_aggreg['ba'])]
-                county2zone['ba'] = county2zone['r'].map(
-                    rb_aggreg.set_index('ba')['aggreg'].to_dict()
-                )
-                # Add BAs associated with aggreg regions to ba_regions list
-                aggreg_regions_2_ba = [
-                    x
-                    for x in rb_aggreg['ba']
-                    if x not in aggreg_regions and x not in county_regions2ba
-                ]
-                ba_regions = list(set(ba_regions + aggreg_regions_2_ba))
-            # Create list of counties that belong to regions being solved at BA
-            BA_county_list = county2zone[county2zone['r'].isin(ba_regions)].copy()
-            BA_county_list.loc[:,'FIPS'] = 'p' + BA_county_list['FIPS'].astype(str)
-            # Map these counties to their BA
-            BA_2_county = BA_county_list.set_index('FIPS')['r'].to_dict()
-            BA_county_list = BA_county_list['FIPS'].tolist()
-
-    ### Procedure for handling single-resolution ReEDS runs
-    else:
-        agglevel = agglevel[0]
-        lvl = 'ba' if agglevel in ['ba', 'aggreg'] else 'county'
-
-        if lvl == 'county':
-            county_regions = hierarchy[hierarchy['resolution'] == 'county']['*r'].to_list()
-            r_ba = pd.read_csv(os.path.join(inputs_case, 'r_ba.csv'))
-            r_ba_dict = r_ba.set_index('r')['ba'].to_dict()
-            # List of BAs associated with county resolution regions
-            county_regions2ba = pd.DataFrame(county_regions)[0].map(r_ba_dict).unique().tolist()
-            transgrp_regions_county = list(
-                set(hierarchy_org[hierarchy_org['ba'].isin(county_regions2ba)]['transgrp'])
-            )
-
-        else:
-            county_regions = []
-            county_regions2ba = []
-            transgrp_regions_county = []
-
-        BA_county_list = []
-        BA_2_county = []
-
-    return {
-        'lvl': lvl,
-        'agglevel': agglevel,
-        'ba_regions': ba_regions,
-        'county_regions': county_regions,
-        'county_regions2ba': county_regions2ba,
-        'BA_county_list': BA_county_list,
-        'BA_2_county': BA_2_county,
-        'ba_transgrp': transgrp_regions_ba,
-        'county_transgrp': transgrp_regions_county,
-    }
-
-
 def assign_to_offshore_zones(unitdata):
     """Map offshore wind units to offshore zones based on lat/lon and zone outlines"""
     ### Get offshore zones
@@ -146,7 +24,7 @@ def assign_to_offshore_zones(unitdata):
     index2offshorezone = dfwind.sjoin_nearest(dfzones, max_distance=1e5)['index_right']
 
     dfout = unitdata.copy()
-    dfout.loc[index2offshorezone.index, 'reeds_ba'] = index2offshorezone.values
+    dfout.loc[index2offshorezone.index, 'r'] = index2offshorezone.values
 
     return dfout
 
@@ -272,18 +150,18 @@ def apply_variable_disaggregation(
         df = df.merge(
             disagg_data,
             left_on=[region_col, 'i'],
-            right_on=['PCA_REG', 'i']
+            right_on=['legacy_ba', 'i']
         )
     else:
         df = df.merge(
-            disagg_data[['PCA_REG', 'FIPS', 'fracdata']],
+            disagg_data[['legacy_ba', 'FIPS', 'fracdata']],
             left_on=region_col,
-            right_on='PCA_REG'
+            right_on='legacy_ba'
         )
 
     # Replace legacy zones in region_col with the county FIPS codes
     df = (
-        df.drop(columns=[region_col, 'PCA_REG'])
+        df.drop(columns=[region_col, 'legacy_ba'])
         .rename(columns={'FIPS': region_col})
     )
 
diff --git a/runreeds.py b/runreeds.py
index e0628622..d76a6149 100644
--- a/runreeds.py
+++ b/runreeds.py
@@ -144,7 +144,7 @@ def get_ivt_numclass(reeds_path, casedir, caseSwitches):
     return numclass
 
 
-def get_rev_paths(revswitches, caseSwitches):
+def get_rev_paths(revswitches):
     # Expand on reV path based on where this run is happening
     # when running on the HPC this links to the shared-projects folder
     hpc = True if (int(os.environ.get('REEDS_USE_SLURM',0))) else False
@@ -169,15 +169,10 @@ def get_rev_paths(revswitches, caseSwitches):
     revswitches['rev_path'] = revswitches.apply(lambda row: os.path.join(row.sc_path, "reV", row.rev_case), axis=1)
 
     # link to the pre-processed reV supply curves from hourlize
-    def get_rev_sc_file_name(caseSwitches, rev_row, use_hpc=False):
+    def get_rev_sc_file_name(rev_row, use_hpc=False):
         if pd.isnull(rev_row.original_sc_file):
             return ""
         else:
-            if caseSwitches['GSw_RegionResolution'] == "county":
-                sc_folder_suffix = "_county"
-            else:
-                sc_folder_suffix = "_ba"
-
             # link to HPC or other sc_path
             if use_hpc:
                 sc_path = rev_row.hpc_sc_path
@@ -186,14 +181,15 @@ def get_rev_sc_file_name(caseSwitches, rev_row, use_hpc=False):
 
             # supply curve name should be in format of {tech}_rev_supply_curves_raw.csv
             # in the hourlize results folder (must match format in 'save_sc_outputs' function of hourlize/resource.py)
-            sc_file = os.path.join(sc_path,
-                            rev_row.tech + "_" + rev_row.access_case + sc_folder_suffix,
-                            "results",
-                            rev_row.tech + "_supply_curve_raw.csv"
-                            )
+            sc_file = os.path.join(
+                sc_path,
+                f"{rev_row.tech}_{rev_row.access_case}_county",
+                "results",
+                f"{rev_row.tech}_supply_curve_raw.csv"
+            )
             return sc_file
-    revswitches['sc_file'] = revswitches.apply(lambda row: get_rev_sc_file_name(caseSwitches, row), axis=1)
-    revswitches['hpc_sc_file'] = revswitches.apply(lambda row: get_rev_sc_file_name(caseSwitches, row, use_hpc=True), axis=1)
+    revswitches['sc_file'] = revswitches.apply(lambda row: get_rev_sc_file_name(row), axis=1)
+    revswitches['hpc_sc_file'] = revswitches.apply(lambda row: get_rev_sc_file_name(row, use_hpc=True), axis=1)
 
     return revswitches
 
@@ -291,27 +287,8 @@ def check_compatibility(sw):
             f"GSw_Region={sw['GSw_Region']}, GSw_GasCurve={sw['GSw_GasCurve']}"
         )
 
-    if sw['GSw_RegionResolution'] in ['county','mixed']:
-        err_switch_configs = []
-        if sw['GSw_LoadAllocationMethod'] == 'state_lpf':
-            err_switch_configs.append('GSw_LoadAllocationMethod=state_lpf')
-
-        if len(err_switch_configs) > 0:
-            raise NotImplementedError(
-                'The following switch configurations are not implemented for '
-                'county/mixed resolution:\n{}\n'
-                .format('\n'.join(err_switch_configs))
-            )
-
     reeds.inputs.validate_zoneset(sw['GSw_ZoneSet'])
 
-    ### Aggregation
-    if (sw['GSw_RegionResolution'] != 'aggreg') and (int(sw['GSw_NumCSPclasses']) != 12):
-        raise NotImplementedError(
-            'Aggregated CSP classes only work with aggregated regions. '
-            'GSw_NumCSPclasses is incompatible with '
-            'GSw_RegionResolution != aggreg')
-
     ### Parsed string switches
     ## Automatic inputs
     reeds_path = os.path.dirname(__file__)
@@ -458,8 +435,7 @@ def check_compatibility(sw):
         raise ValueError(err)
 
     # Add a row for each county
-    ## TEMPORARY 20260402 until the aggregation procedure is updated
-    county2zone = reeds.io.get_county2zone(GSw_ZoneSet='z134', as_map=False)
+    county2zone = reeds.io.get_county2zone(GSw_ZoneSet=sw['GSw_ZoneSet'], as_map=False)
     county2zone['county'] = 'p' + county2zone.FIPS
     # Add county info to hierarchy
     hierarchy = hierarchy.merge(county2zone.drop(columns=['FIPS','state']), on='r')
@@ -1158,7 +1134,7 @@ def write_batch_script(
     revswitches = revswitches.merge(binSwitches, on=['tech'], how='left')
 
     # format rev paths
-    revswitches = get_rev_paths(revswitches, caseSwitches)
+    revswitches = get_rev_paths(revswitches)
 
     # save rev paths file for run
     revswitches[['tech','access_switch','access_case','rev_case','bins','sc_path',