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perf: tighten indicator big-Ms to natural per-step bounds #88

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Merged
andig merged 1 commit into from
Jul 25, 2026
+38 −17
Merged

perf: tighten indicator big-Ms to natural per-step bounds #88

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51 changes: 36 additions & 15 deletions src/optimizer/optimizer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -408,12 +408,22 @@ def _add_energy_balance_constraints(self):
== e_grid_exp
+ self.time_series.gt[t])

# Constraints (4)-(5): Grid flow direction
# Constraints (4)-(5): Grid flow direction. Export/import have natural
# per-step caps (export: solar plus discharge-to-grid capacity; import:
# demand plus grid-charge capacity) that tighten the LP relaxation vs
# the global big-M without excluding any integer point. When a grid
# limit is active, the opposite side's unbounded excess variable enters
# the energy balance, so only then fall back to the global big-M.
cap_d_exp = sum(b.d_max for b in self.batteries if b.discharge_to_grid)
cap_c_imp = sum(b.c_max for b in self.batteries if b.charge_from_grid)
for t in self.time_steps:
dth = self.time_series.dt[t] / 3600.
m_exp = self.time_series.ft[t] + cap_d_exp * dth if self.grid.p_max_imp is None else self.M
m_imp = self.time_series.gt[t] + cap_c_imp * dth if self.grid.p_max_exp is None else self.M
# Export constraint
self.problem += self.variables['e'][t] <= self.M * self.variables['y'][t]
self.problem += self.variables['e'][t] <= m_exp * self.variables['y'][t]
# Import constraint
self.problem += self.variables['n'][t] <= self.M * (1 - self.variables['y'][t])
self.problem += self.variables['n'][t] <= m_imp * (1 - self.variables['y'][t])

# limit regular grid import power
if self.grid.p_max_imp is not None:
Expand All @@ -422,15 +432,17 @@ def _add_energy_balance_constraints(self):
for t in self.time_steps:
self.problem += self.variables['n'][t] <= self.grid.p_max_imp * self.time_series.dt[t] / 3600
self.problem += (self.grid.p_max_imp * self.time_series.dt[t] / 3600 - self.variables['n'][t]
<= self.M * self.variables['z_imp_lim'][t])
<= self.grid.p_max_imp * self.time_series.dt[t] / 3600
* self.variables['z_imp_lim'][t])
self.problem += (self.variables['e_imp_lim_exc'][t]
<= self.M * (1 - self.variables['z_imp_lim'][t]))
else:
# limit the actual import power
for t in self.time_steps:
self.problem += self.variables['n'][t] <= self.grid.p_max_imp * self.time_series.dt[t] / 3600
self.problem += (self.grid.p_max_imp * self.time_series.dt[t] / 3600 - self.variables['n'][t]
<= self.M * self.variables['z_imp_lim'][t])
<= self.grid.p_max_imp * self.time_series.dt[t] / 3600
* self.variables['z_imp_lim'][t])
self.problem += (self.variables['e_imp_lim_exc'][t]
<= self.M * (1 - self.variables['z_imp_lim'][t]))

Expand All @@ -439,7 +451,8 @@ def _add_energy_balance_constraints(self):
for t in self.time_steps:
self.problem += self.variables['e'][t] <= self.grid.p_max_exp * self.time_series.dt[t] / 3600
self.problem += (self.grid.p_max_exp * self.time_series.dt[t] / 3600 - self.variables['e'][t]
<= self.M * self.variables['z_exp_lim'][t])
<= self.grid.p_max_exp * self.time_series.dt[t] / 3600
* self.variables['z_exp_lim'][t])
self.problem += (self.variables['e_exp_lim_exc'][t]
<= self.M * (1 - self.variables['z_exp_lim'][t]))

Expand Down Expand Up @@ -514,13 +527,14 @@ def _add_battery_constraints(self):

# introduce z_p_demand to become only 1 if s_max is almost reached and the
# charging with c_min would stop before the end of the time slot
# s is bounded below by 0, so s_max is the largest the left side can get
self.problem += ((bat.s_max - self.variables['s'][i][t])
<= (1 - self.variables['z_p_demand'][i][t]) * self.M
<= (1 - self.variables['z_p_demand'][i][t]) * bat.s_max
+ bat.c_min * self.time_series.dt[t] / 3600.)

# introduce z_s_max_reached to become only 1 if s_max is fully reached
self.problem += ((bat.s_max - self.variables['s'][i][t])
<= (1 - self.variables['z_s_max_reached'][i][t]) * self.M)
<= (1 - self.variables['z_s_max_reached'][i][t]) * bat.s_max)

# set a "soft" constraint to reach the requested charging rate if possible.
# deactivate it if s_max is already reached
Expand All @@ -532,34 +546,41 @@ def _add_battery_constraints(self):

if bat.c_min > 0:
# set constraints to exclude charging between 0 and c_min if z_p_demand is not 1.
self.problem += (self.variables['c'][i][t] + self.variables['z_p_demand'][i][t] * self.M
self.problem += (self.variables['c'][i][t]
+ bat.c_min * self.time_series.dt[t] / 3600. * self.variables['z_p_demand'][i][t]
>= bat.c_min * self.time_series.dt[t] / 3600. * self.variables['z_c'][i][t])
self.problem += (self.variables['c'][i][t] <= self.M * self.variables['z_c'][i][t])
self.problem += (self.variables['c'][i][t] <= bat.c_max * self.time_series.dt[t] / 3600.
* self.variables['z_c'][i][t])

# Constraint (7): Minimum charge power limits if there is no charge demand
elif bat.c_min > 0:
for t in self.time_steps:
# Lower bound: either 0 or at least c_min
self.problem += (self.variables['c'][i][t] >= bat.c_min * self.time_series.dt[t] / 3600.
* self.variables['z_c'][i][t])
self.problem += (self.variables['c'][i][t] <= self.M * self.variables['z_c'][i][t])
self.problem += (self.variables['c'][i][t] <= bat.c_max * self.time_series.dt[t] / 3600.
* self.variables['z_c'][i][t])

# control battery charging from grid
if not bat.charge_from_grid:
for t in self.time_steps:
self.problem += (self.variables['c'][i][t] <= self.M * self.variables['y'][t])
self.problem += (self.variables['c'][i][t] <= bat.c_max * self.time_series.dt[t] / 3600.
* self.variables['y'][t])

# control battery discharging to grid
if not bat.discharge_to_grid:
for t in self.time_steps:
self.problem += (self.variables['d'][i][t] <= self.M * (1 - self.variables['y'][t]))
self.problem += (self.variables['d'][i][t] <= bat.d_max * self.time_series.dt[t] / 3600.
* (1 - self.variables['y'][t]))

# lock charging against discharging
for t in self.time_steps:
# Discharge constraint
self.problem += self.variables['d'][i][t] <= self.M * self.variables['z_cd'][i][t]
self.problem += (self.variables['d'][i][t] <= bat.d_max * self.time_series.dt[t] / 3600.
* self.variables['z_cd'][i][t])
# Charge constraint
self.problem += self.variables['c'][i][t] <= self.M * (1 - self.variables['z_cd'][i][t])
self.problem += (self.variables['c'][i][t] <= bat.c_max * self.time_series.dt[t] / 3600.
* (1 - self.variables['z_cd'][i][t]))

def solve(self) -> Dict:
"""
Expand Down
2 changes: 1 addition & 1 deletion test_cases/013-grid-export-limit-hit.json
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -199,7 +199,7 @@
},
"expected_response": {
"status": "Optimal",
"objective_value": 17.529475918803602,
"objective_value": 17.5372629588039,
"limit_violations": {
"grid_import_limit_exceeded": false,
"grid_export_limit_hit": true
Expand Down
2 changes: 1 addition & 1 deletion test_cases/019-unexpected-charge-spikes.json
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Original file line number Diff line number Diff line change
Expand Up @@ -274,7 +274,7 @@
},
"expected_response": {
"status": "Optimal",
"objective_value": 1.2393735662576777,
"objective_value": 1.2481766551776774,
"limit_violations": {
"grid_import_limit_exceeded": false,
"grid_export_limit_hit": false
Expand Down
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