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feat: Direktvermarktung mit Batterie-Netzeinspeisung

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Fügt einen Direktvermarktungs-Modus (feedintariff.direct_marketing_enabled)
hinzu, der den Börsenpreis als Einspeisevergütung nutzt und aktive
Batterie-Entladung ins Netz (battery_grid_export_allowed) sowie
DC-Charge-Bypass optimiert.

- FeedInTariffEnergyCharts-Provider (Börsen-Einspeisetarif inkl. Prognose)
- Inverter: DC/AC-Wirkungsgrade und Batterie-Grid-Export in process_energy
- Genetik: Export-/DC-Charge-Zustände, Restwert-Bewertung des Akkus
- Solution-Result: neues Feld Feed_in_tariff (verwendeter Tarif je Stunde)
- Tests für neue Provider, Solution und Simulation

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
This commit is contained in:
Andreas
2026-07-12 09:01:33 +02:00
co-authored by Claude Fable 5
parent cc583600d8
commit 7f2ac9098c
19 changed files with 960 additions and 72 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/akkudoktoreos/optimization/genetic/geneticsolution.py
+69 -16
View File
@@ -130,6 +130,12 @@ class GeneticSimulationResult(GeneticParametersBaseModel):
Electricity_price: list[float] = Field(
json_schema_extra={"description": "Used Electricity Price, including predictions"}
)
Feed_in_tariff: list[float] = Field(
default_factory=list,
json_schema_extra={
"description": "Used feed-in tariff in €/Wh per hour, including predictions"
},
)
@field_validator(
"Last_Wh_pro_Stunde",
@@ -142,6 +148,7 @@ class GeneticSimulationResult(GeneticParametersBaseModel):
"Verluste_Pro_Stunde",
"Home_appliance_wh_per_hour",
"Electricity_price",
"Feed_in_tariff",
mode="before",
)
def convert_numpy(cls, field: Any) -> Any:
@@ -163,7 +170,13 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
)
discharge_allowed: list[int] = Field(
json_schema_extra={
"description": "Array with discharge values (1 for discharge, 0 otherwise)."
"description": "Array with self-consumption discharge values (1 for discharge, 0 otherwise)."
}
)
battery_grid_export_allowed: list[int] = Field(
default_factory=list,
json_schema_extra={
"description": "Array with battery-to-grid export values (1 for export discharge, 0 otherwise)."
}
)
eautocharge_hours_float: Optional[list[float]] = Field(json_schema_extra={"description": "TBD"})
@@ -186,6 +199,7 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
"ac_charge",
"dc_charge",
"discharge_allowed",
"battery_grid_export_allowed",
mode="before",
)
def convert_numpy(cls, field: Any) -> Any:
@@ -226,13 +240,15 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
ac_charge: float,
dc_charge: float,
discharge_allowed: bool,
battery_grid_export_allowed: bool = False,
) -> tuple[BatteryOperationMode, float]:
"""Maps low-level solution to a representative operation mode and factor.
Args:
ac_charge (float): Allowed AC-side charging power (relative units).
dc_charge (float): Allowed DC-side charging power (relative units).
discharge_allowed (bool): Whether discharging is permitted.
discharge_allowed (bool): Whether discharging to local load is permitted.
battery_grid_export_allowed (bool): Whether discharge into the grid is permitted.
Returns:
tuple[BatteryOperationMode, float]: A tuple containing
@@ -240,15 +256,28 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
- `float`: the operation factor corresponding to the active signal.
Notes:
- The mapping prioritizes AC charge > DC charge > discharge.
- Explicit grid export is separate from local-load discharge.
- The mapping prioritizes export > AC charge > DC charge > discharge.
- Multiple strategies can produce the same low-level signals; this function
returns a representative mode based on a defined priority order.
"""
# (0,0,0) → Nothing allowed
if ac_charge <= 0.0 and dc_charge <= 0.0 and not discharge_allowed:
if (
ac_charge <= 0.0
and dc_charge <= 0.0
and not discharge_allowed
and not battery_grid_export_allowed
):
return BatteryOperationMode.IDLE, 1.0
# (0,0,1) → Discharge only
if battery_grid_export_allowed:
if ac_charge > 0.0 or dc_charge > 0.0:
raise ValueError(
"Illegal state: battery_grid_export_allowed cannot be combined with charging"
)
return BatteryOperationMode.GRID_SUPPORT_EXPORT, 1.0
# (0,0,1) -> Discharge for local load only
if ac_charge <= 0.0 and dc_charge <= 0.0 and discharge_allowed:
return BatteryOperationMode.PEAK_SHAVING, 1.0
@@ -289,7 +318,8 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
dc_charge: float,
discharge_allowed: bool,
soc_pct: float,
) -> tuple[float, float, bool]:
battery_grid_export_allowed: bool = False,
) -> tuple[float, float, bool, bool]:
"""Clamp raw genetic gene values by the battery's actual SOC at that hour.
The raw gene values represent the optimizer's *intent* and are stored
@@ -305,10 +335,11 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
- DC charge factor (PV): zeroed when battery is at or above max SOC
(the inverter curtails automatically, but this makes intent clear).
- Discharge: blocked when SOC is at or below min SOC.
- Battery grid export: blocked when SOC is at or below min SOC.
"""
bat_list = self.config.devices.batteries
if not bat_list:
return ac_charge, dc_charge, discharge_allowed
return ac_charge, dc_charge, discharge_allowed, battery_grid_export_allowed
bat = bat_list[0]
min_soc = float(bat.min_soc_percentage)
@@ -341,19 +372,22 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
# --- Discharge: block at min SOC ---
effective_dis = discharge_allowed and (soc_pct > min_soc)
effective_grid_export = battery_grid_export_allowed and (soc_pct > min_soc)
return effective_ac, effective_dc, effective_dis
return effective_ac, effective_dc, effective_dis, effective_grid_export
def optimization_solution(self) -> OptimizationSolution:
"""Provide the genetic solution as a general optimization solution.
The battery modes are controlled by the grid control triggers:
- ac_charge: charge from grid
- discharge_allowed: discharge to grid
- discharge_allowed: discharge to local load
- battery_grid_export_allowed: discharge to grid
The following battery modes are supported:
- SELF_CONSUMPTION: ac_charge == 0 and discharge_allowed == 0
- GRID_SUPPORT_EXPORT: ac_charge == 0 and discharge_allowed == 1
- SELF_CONSUMPTION: dc_charge > 0 and discharge_allowed == 1
- PEAK_SHAVING: ac_charge == 0 and discharge_allowed == 1
- GRID_SUPPORT_EXPORT: battery_grid_export_allowed == 1
- GRID_SUPPORT_IMPORT: ac_charge > 0 and discharge_allowed == 0 or 1
"""
start_datetime = get_ems().start_datetime
@@ -407,6 +441,7 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
"genetic_ac_charge_factor": [],
"genetic_dc_charge_factor": [],
"genetic_discharge_allowed_factor": [],
"genetic_battery_grid_export_allowed_factor": [],
}
# ac_charge, dc_charge, discharge_allowed start at hour 0 of start day
for hour_idx, rate in enumerate(self.ac_charge):
@@ -417,11 +452,19 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
ac_charge_hour = self.ac_charge[hour_idx]
dc_charge_hour = self.dc_charge[hour_idx]
discharge_allowed_hour = bool(self.discharge_allowed[hour_idx])
battery_grid_export_allowed_hour = (
bool(self.battery_grid_export_allowed[hour_idx])
if hour_idx < len(self.battery_grid_export_allowed)
else False
)
# Raw genetic gene values — optimizer intent, stored verbatim
operation["genetic_ac_charge_factor"].append(ac_charge_hour)
operation["genetic_dc_charge_factor"].append(dc_charge_hour)
operation["genetic_discharge_allowed_factor"].append(float(discharge_allowed_hour))
operation["genetic_battery_grid_export_allowed_factor"].append(
float(battery_grid_export_allowed_hour)
)
# SOC-clamped effective values — what can physically be executed at
# this hour given the expected battery state of charge.
@@ -431,11 +474,15 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
if result_idx < len(self.result.akku_soc_pro_stunde)
else 0.0
)
eff_ac, eff_dc, eff_dis = self._soc_clamped_operation_factors(
ac_charge_hour, dc_charge_hour, discharge_allowed_hour, soc_h_pct
eff_ac, eff_dc, eff_dis, eff_grid_export = self._soc_clamped_operation_factors(
ac_charge_hour,
dc_charge_hour,
discharge_allowed_hour,
soc_h_pct,
battery_grid_export_allowed_hour,
)
operation_mode, operation_mode_factor = self._battery_operation_from_solution(
eff_ac, eff_dc, eff_dis
eff_ac, eff_dc, eff_dis, eff_grid_export
)
for mode in BatteryOperationMode:
mode_key = f"{battery_device_id}_{mode.lower()}_op_mode"
@@ -671,14 +718,20 @@ class GeneticSolution(ConfigMixin, GeneticParametersBaseModel):
if result_idx < len(self.result.akku_soc_pro_stunde)
else 0.0
)
eff_ac, eff_dc, eff_dis = self._soc_clamped_operation_factors(
battery_grid_export_allowed_hour = (
bool(self.battery_grid_export_allowed[hour_idx])
if hour_idx < len(self.battery_grid_export_allowed)
else False
)
eff_ac, eff_dc, eff_dis, eff_grid_export = self._soc_clamped_operation_factors(
self.ac_charge[hour_idx],
self.dc_charge[hour_idx],
bool(self.discharge_allowed[hour_idx]),
soc_h_pct,
battery_grid_export_allowed_hour,
)
operation_mode, operation_mode_factor = self._battery_operation_from_solution(
eff_ac, eff_dc, eff_dis
eff_ac, eff_dc, eff_dis, eff_grid_export
)
if (
operation_mode == last_operation_mode