feat: per-battery charge/discharge efficiency

openapi.yaml

@@ -269,6 +269,18 @@ components:
           maximum: 2
           default: 0
           description: Charging and discharging priority 0..2 compared to other batteries. 2 = highest priority.
+        eta_c:
+          type: number
+          minimum: 0
+          maximum: 1
+          description: Charging efficiency (0 to 1). Overrides the top level eta_c for this battery.
+          example: 0.95
+        eta_d:
+          type: number
+          minimum: 0
+          maximum: 1
+          description: Discharging efficiency (0 to 1). Overrides the top level eta_d for this battery.
+          example: 0.95
 
     TimeSeries:
       type: object
@@ -342,14 +354,14 @@ components:
           minimum: 0
           maximum: 1
           default: 0.95
-          description: Charging efficiency (0 to 1)
+          description: Default charging efficiency (0 to 1) for batteries without their own eta_c
           example: 0.95
         eta_d:
           type: number
           minimum: 0
           maximum: 1
           default: 0.95
-          description: Discharging efficiency (0 to 1)
+          description: Default discharging efficiency (0 to 1) for batteries without their own eta_d
           example: 0.95
 
     BatteryResult:

src/optimizer/app.py

@@ -80,7 +80,9 @@ def handle_validation_error(error):
     'c_max': fields.Float(required=True, description='Maximum charge power (W)'),
     'd_max': fields.Float(required=True, description='Maximum discharge power (W)'),
     'p_a': fields.Float(required=True, description='Monetary value per Wh at end of the optimization horizon'),
-    'c_priority': fields.Integer(required=False, description='Charging and discharging priority compared to other batteries. 2 = highest priority.')
+    'c_priority': fields.Integer(required=False, description='Charging and discharging priority compared to other batteries. 2 = highest priority.'),
+    'eta_c': fields.Float(required=False, description='Charging efficiency (0 to 1), overrides the top level default'),
+    'eta_d': fields.Float(required=False, description='Discharging efficiency (0 to 1), overrides the top level default')
 })
 
 time_series_model = api.model('TimeSeries', {
@@ -96,8 +98,8 @@ def handle_validation_error(error):
     'grid': fields.Nested(grid_model, required=False, description='Grid import and export configuration'),
     'batteries': fields.List(fields.Nested(battery_config_model), required=True, description='Battery configurations'),
     'time_series': fields.Nested(time_series_model, required=True, description='Time series data'),
-    'eta_c': fields.Float(required=False, default=0.95, description='Charging efficiency'),
-    'eta_d': fields.Float(required=False, default=0.95, description='Discharging efficiency'),
+    'eta_c': fields.Float(required=False, default=0.95, description='Default charging efficiency for batteries without their own eta_c'),
+    'eta_d': fields.Float(required=False, default=0.95, description='Default discharging efficiency for batteries without their own eta_d'),
 })
 
 # Output models
@@ -155,6 +157,8 @@ def post(self):
             )
 
             # Parse battery configurations
+            eta_c_default = data.get('eta_c', 0.95)
+            eta_d_default = data.get('eta_d', 0.95)
             batteries = []
             for bat_data in data['batteries']:
                 batteries.append(BatteryConfig(
@@ -171,6 +175,8 @@ def post(self):
                     d_max=bat_data['d_max'],
                     p_a=bat_data['p_a'],
                     c_priority=bat_data.get('c_priority', 0),
+                    eta_c=bat_data.get('eta_c', eta_c_default),
+                    eta_d=bat_data.get('eta_d', eta_d_default),
                 ))
 
             # Parse time series data
@@ -209,8 +215,6 @@ def post(self):
                 grid=grid,
                 batteries=batteries,
                 time_series=time_series,
-                eta_c=data.get('eta_c', 0.95),
-                eta_d=data.get('eta_d', 0.95),
                 M=1e6
             )
 

src/optimizer/optimizer.py

@@ -36,6 +36,8 @@ class BatteryConfig:
     p_demand: Optional[List[float]] = None  # Minimum charge demand (Wh)
     s_goal: Optional[List[float]] = None  # Goal state of charge (Wh)
     c_priority: int = 0
+    eta_c: float = 0.95  # Charging efficiency (0 to 1)
+    eta_d: float = 0.95  # Discharging efficiency (0 to 1)
 
 
 @dataclass
@@ -54,7 +56,7 @@ class Optimizer:
     """
 
     def __init__(self, strategy: OptimizationStrategy, grid: GridConfig, batteries: List[BatteryConfig], time_series: TimeSeriesData,
-                 eta_c: float = 0.95, eta_d: float = 0.95, M: float = 1e6, optimizer_settings: OptimizerSettings | None = None):
+                 M: float = 1e6, optimizer_settings: OptimizerSettings | None = None):
         """
         Optimizer Constructor
         """
@@ -65,8 +67,6 @@ def __init__(self, strategy: OptimizationStrategy, grid: GridConfig, batteries:
         self.grid = grid
         self.batteries = batteries
         self.time_series = time_series
-        self.eta_c = eta_c
-        self.eta_d = eta_d
         self.M = M
         # number of time steps
         self.T = len(time_series.gt)
@@ -427,15 +427,15 @@ def _add_battery_constraints(self):
             if len(self.time_steps) > 0:
                 self.problem += (self.variables['s'][i][0]
                                  == bat.s_initial
-                                 + self.eta_c * self.variables['c'][i][0]
-                                 - (1 / self.eta_d) * self.variables['d'][i][0])
+                                 + bat.eta_c * self.variables['c'][i][0]
+                                 - (1 / bat.eta_d) * self.variables['d'][i][0])
 
             # State of charge evolution
             for t in range(1, self.T):
                 self.problem += (self.variables['s'][i][t]
                                  == self.variables['s'][i][t - 1]
-                                 + self.eta_c * self.variables['c'][i][t]
-                                 - (1 / self.eta_d) * self.variables['d'][i][t])
+                                 + bat.eta_c * self.variables['c'][i][t]
+                                 - (1 / bat.eta_d) * self.variables['d'][i][t])
 
             # Constraint (6): Battery SOC goal constraints (for t > 0)
             if bat.s_goal is not None:

tests/test_app.py

@@ -36,6 +36,37 @@ def test_optimizer(test_case: pathlib.Path):
             f"objective value: {actual_objective_value}, expected was: {expected_objective_value}"
 
 
+def test_per_battery_efficiency():
+    # both batteries are forced to charge the same energy, so their state of charge
+    # gain must scale with their individual charging efficiency
+    client = app.test_client()
+    battery = {
+        "charge_from_grid": True,
+        "s_min": 0, "s_max": 10000, "s_initial": 0,
+        "c_min": 0, "c_max": 2000, "d_max": 0, "p_a": 0.01,
+        "p_demand": [1000, 0],
+    }
+    request = {
+        "batteries": [
+            {**battery, "eta_c": 1.0},
+            {**battery, "eta_c": 0.5},
+        ],
+        "time_series": {
+            "dt": [3600, 3600],
+            "gt": [0, 0],
+            "ft": [0, 0],
+            "p_N": [0.3, 0.3],
+            "p_E": [0.3, 0.3],
+        },
+    }
+    response = client.post("/optimize/charge-schedule", json=request)
+
+    assert response.status_code == 200
+    assert response.json["status"] == "Optimal"
+    assert numpy.isclose(response.json["batteries"][0]["state_of_charge"][0], 1000)
+    assert numpy.isclose(response.json["batteries"][1]["state_of_charge"][0], 500)
+
+
 def test_abort_returns_json_message():
     # message-only api.abort(400, ...) must return a JSON body, not an empty response
     client = app.test_client()