[ClimateHydro] Apply Climate Adjustment Factors to Hydropower CF in Input Processing

reeds/core/setup/b_inputs.gms

@@ -4109,24 +4109,6 @@ fuel_price(i,r,t)$[sum{f$fuel2tech(f,i),1}$(not fuel_price(i,r,t))] =
 fuel_price(i,r,t)$upgrade(i) = sum{ii$upgrade_to(i,ii), fuel_price(ii,r,t) } ;
 
 
-*=====================================================
-* -- Climate impacts on nondispatchable hydropower --
-*=====================================================
-
-$ifthen.climatehydro %GSw_ClimateHydro% == 1
-
-* declared over allt to allow for external data files that extend beyond end_year
-* Written by climateprep.py
-table climate_hydro_annual(r,allt)  "annual dispatchable hydropower availability"
-$offlisting
-$ondelim
-$include inputs_case%ds%climate_hydadjann.csv
-$offdelim
-$onlisting
-;
-$endif.climatehydro
-
-
 *=====================================================
 * -- Climate impacts on nondispatchable hydropower --
 *=====================================================

reeds/core/solve/2_temporal_params.gms

@@ -472,29 +472,6 @@ $onlisting
 / ;
 $offempty
 
-$ifthen.climatehydro %GSw_ClimateHydro% == 1
-
-* Written by climateprep.py
-table climate_hydro_seasonal(r,allszn,allt)  "annual/seasonal nondispatchable hydropower availability"
-$offlisting
-$ondelim
-$include inputs_case%ds%%temporal_inputs%%ds%climate_hydadjsea.csv
-$offdelim
-$onlisting
-;
-
-* adjust cf_hyd based on annual/seasonal climate multipliers
-* non-dispatchable hydro gets new seasonal profiles as well as annually-varying CF
-* dispatchable hydro keeps the original seasonal profiles; only annual CF changes. Reflects the assumption
-* that reservoirs will be utilized in the same seasonal pattern even if seasonal inflows change.
-cf_hyd(i,szn,r,t)$[hydro_nd(i)$(yeart(t)>=Sw_ClimateStartYear)] =
-    sum{allt$att(allt,t), cf_hyd(i,szn,r,t) * climate_hydro_seasonal(r,szn,allt) } ;
-
-cf_hyd(i,szn,r,t)$[hydro_d(i)$(yeart(t)>=Sw_ClimateStartYear)]  =
-    sum{allt$att(allt,t), cf_hyd(i,szn,r,t) * climate_hydro_annual(r,allt) } ;
-
-$endif.climatehydro
-
 *created by reeds/input_processing/writecapdat.py
 parameter cap_hyd_szn_adj(i,allszn,r) "--fraction-- seasonal max capacity adjustment for dispatchable hydro"
 /

reeds/input_processing/climateprep.py

@@ -181,21 +181,19 @@ def readwrite(
         ## Drop extra data after the model end year
         .loc[:,:endyear]
     )
-
-    # Files indexed by month undergo additional processing in hourly_writetimeseries. Create
-    # intermediate filenames for these files and melt them back to long format
-    file_prefix = 'temp' if 'month' in dfout.index.names else 'climate'
-    keepindex = False if file_prefix == 'temp' else True
-    if file_prefix == 'temp': 
-        dfout = pd.melt(
-            dfout.reset_index(), id_vars=index[infile], value_vars=dfout.columns,
-            var_name='t', value_name='Value'
-        )
-
+    # Melt to long format
+    dfout = pd.melt(
+        dfout.reset_index(), id_vars=index[infile], value_vars=dfout.columns,
+        var_name='t', value_name='Value'
+    )
+    # ClimateWater files indexed by month undergo additional processing in hourly_writetimeseries -
+    # Create intermediate filenames for these files
+    file_prefix = 'temp' if infile in ['UnappWaterMult','UnappWaterSeaAnnDistr'] else 'climate'
     # Write it to output folder
     dfout.round(decimals).to_csv(os.path.join(inputs_case, f'{file_prefix}_{infile}.csv'),
-                                 index=keepindex)
-
+                                 index=False)
+
+
     return dfout
 
 

reeds/input_processing/hourly_writetimeseries.py

@@ -232,7 +232,6 @@ def format_climate_inputs(filename, inputs_case, szn_month_weights):
         szn_month_weights
         """
         climate_index = {
-            'temp_hydadjsea': ['r','season','t'],
             'temp_UnappWaterMult': ['wst','r','season','t'],
             'temp_UnappWaterSeaAnnDistr': ['wst','r','season','t']
         }
@@ -1105,10 +1104,8 @@ def main(sw, reeds_path, inputs_case, periodtype='rep', make_plots=1, logging=Tr
         .rename(columns={"season": "szn"})
     )
 
-    ### Import and format monthly climate_{hydadjsea/UnappWaterMult/UnappWaterSeaAnnDistr}.csv
+    ### Import and format monthly climate_{UnappWaterMult/UnappWaterSeaAnnDistr}.csv
     climate_files = {}   
-    if int(sw.GSw_ClimateHydro):
-        climate_files['temp_hydadjsea'] = format_climate_inputs('temp_hydadjsea', inputs_case, szn_month_weights)
     if int(sw.GSw_ClimateWater):
         for file in ['temp_UnappWaterMult', 'temp_UnappWaterSeaAnnDistr']:
             climate_files[file] = format_climate_inputs(file, inputs_case, szn_month_weights)
@@ -1532,10 +1529,7 @@ def main(sw, reeds_path, inputs_case, periodtype='rep', make_plots=1, logging=Tr
         "peak_h": [pd.DataFrame(columns=["*r", "h", "t", "MW"]), True, False],
     }
 
-    # Add climate inputs based on GSw_Climate* switch selection
-    if int(sw.GSw_ClimateHydro):
-        ## Climate-adjusted annual/seasonal nondispatchable hydropower availability
-        write['climate_hydadjsea'] = [climate_files['temp_hydadjsea'], True, True]
+    # Add climate inputs to write dictionary based on GSw_ClimateWater
     if int(sw.GSw_ClimateWater):
         ## Climate-adjusted time-varying annual/seasonal water supply
         write['climate_UnappWaterMult'] = [climate_files['temp_UnappWaterMult'], True, True]

reeds/input_processing/hydcf.py

@@ -403,6 +403,60 @@ def assemble_hydcf(
 
     return hydcf
 
+def apply_hydro_climate_adjustments(
+    hydcf_unadjusted: pd.DataFrame,
+    inputs_case: str
+) -> pd.DataFrame:
+    """
+    Applies climate adjustment factors to hydropower capacity factors, if applicable
+
+    Args:
+        hydcf_unadjusted: Monthly regional CFs prior to climate adjustments
+        inputs_case: Path to the inputs case directory.
+    Returns:
+        pd.DataFrame
+    """
+    # Exit function if climate adjustments to hydropower are turned OFF, otherwise continue
+    sw = reeds.io.get_switches(inputs_case)
+    if not int(sw.GSw_ClimateHydro):
+        return
+
+    # Get sets for dispatchable/non-dispatchable hydro from tech subset table
+    tech_subsets = pd.read_csv(
+        os.path.join(inputs_case, 'tech-subset-table.csv'),
+        index_col=0
+    )
+    hydro_d = set(tech_subsets.loc[tech_subsets['HYDRO_D']=='YES'].index)
+    hydro_nd = set(tech_subsets.loc[tech_subsets['HYDRO_ND']=='YES'].index)
+
+    # Separate data into dispatchable vs non-dispatchable hydropower
+    hydcf_d = hydcf_unadjusted[hydcf_unadjusted.index.isin(hydro_d, level='*i')].reset_index().copy()
+    hydcf_nd = hydcf_unadjusted[hydcf_unadjusted.index.isin(hydro_nd, level='*i')].reset_index().copy()
+    assert len(hydcf_d)+len(hydcf_nd) == len(hydcf_unadjusted), "At least 1 hydro tech is unaccounted for from hydcf.csv"
+
+    # Read hydropower CF climate adjustments and melt to long form      
+    adj_factors_ann = pd.read_csv(
+        os.path.join(inputs_case, 'climate_hydadjann.csv'),
+        dtype={'r':str,'t':int}
+    ).rename(columns={'Value':'Factor'})
+    adj_factors_sea = pd.read_csv(
+        os.path.join(inputs_case, 'climate_hydadjsea.csv'),
+        dtype={'r':str,'t':int,'month':str}
+    ).rename(columns={'Value':'Factor'})
+
+    # Apply adjustment factors
+    hydcf_d = pd.merge(hydcf_d, adj_factors_ann, how='left', on=['r','t'])
+    hydcf_d['value_adj'] = hydcf_d['value'] * hydcf_d['Factor']
+    hydcf_d = hydcf_d.drop(columns=['value','Factor']).rename(columns={'value_adj':'value'})
+    hydcf_nd = pd.merge(hydcf_nd, adj_factors_sea, how='left', on=['r','month','t'])
+    hydcf_nd['value_adj'] = hydcf_nd['value'] * hydcf_nd['Factor']
+    hydcf_nd = hydcf_nd.drop(columns=['value','Factor']).rename(columns={'value_adj':'value'})
+
+    # Reassemble hydcf
+    hydcf = pd.concat([hydcf_d,hydcf_nd],axis=0)
+
+
+    return hydcf
 
 #%% ===========================================================================
 ### --- MAIN FUNCTION ---
@@ -431,6 +485,11 @@ def main(reeds_path, inputs_case):
         future_monthly_regional_cf,
         inputs_case
     )
+    hydcf = apply_hydro_climate_adjustments(
+        hydcf,
+        inputs_case
+    )
+
     hydcf.to_csv(os.path.join(inputs_case, 'hydcf.csv'))
 
 
@@ -455,6 +514,12 @@ def main(reeds_path, inputs_case):
     reeds_path = args.reeds_path
     inputs_case = args.inputs_case
 
+    # #%% Settings for testing
+    # reeds_path = reeds.io.reeds_path
+    # inputs_case = os.path.join(
+    #     reeds_path,'runs',
+    #     'InstantiateRepo_USA_defaults','inputs_case')
+
     #%% Set up logger
     log = reeds.log.makelog(
         scriptname=__file__,
@@ -468,3 +533,5 @@ def main(reeds_path, inputs_case):
         path=os.path.join(inputs_case,'..'))
 
     print('Finished hydcf.py')
+
+# %%

reeds/input_processing/runfiles.csv

@@ -113,6 +113,8 @@ heat_rate_mult.csv,inputs/waterclimate/heat_rate_mult.csv,int(sw.GSw_WaterMain)
 heat_rate_penalty_spin.csv,inputs/plant_characteristics/heat_rate_penalty_spin.csv,1,ignore,ignore,,,,,0,,,,,,
 hintage_char.csv,inputs/sets/hintage_char.csv,1,ignore,ignore,,,,,,,,set,hintage_char,characteristics available in hintage_data,
 hyd_add_upg_cap.csv,inputs/supply_curve/hyd_add_upg_cap.csv,int(sw.GSw_HydroCapEnerUpgradeType) == 2,sum,hydroexist,r,"i,rscbin,wide",,1,0,,,,,,
+hydadjann.csv,inputs/climate/{climatescen}/hydadjann.csv,int(sw.GSw_ClimateHydro) != 0,mean,uniform,r,t,,0,0,,,,,,
+hydadjsea.csv,inputs/climate/{climatescen}/hydadjsea.csv,int(sw.GSw_ClimateHydro) != 0,mean,uniform,r,"month,t",,0,0,,,,,,
 hyd_fom.csv,inputs/hydro/hyd_fom.csv,1,mean,uniform,wide,i,,1,0,,,,,,
 hydcap.csv,inputs/supply_curve/hydcap.csv,1,sum,geosize,wide,"tech,class",,1,0,,,,,,
 hydcapadj.csv,inputs/hydro/SeaCapAdj_hy.csv,1,mean,uniform,r,"*i,month",,0,0,,,,,,

runreeds.py

@@ -1302,6 +1302,7 @@ def write_batch_script(
         for s in [
             'copy_files',
             'mcs_sampler',
+            'climateprep',            
             'hydcf',
             'h2_storage',
             'calc_financial_inputs',
@@ -1310,7 +1311,6 @@ def write_batch_script(
             'writesupplycurves',
             'writedrshift',
             'plantcostprep',
-            'climateprep',
             'hourly_load',
             'recf',
             'forecast',