Issue FlexMeasures#618 Step1-3 done

flexmeasures/cli/data_add.py

@@ -941,6 +941,20 @@ def create_schedule(ctx):
     required=False,
     help="Optimize production against this sensor. Defaults to the consumption price sensor. The sensor typically records an electricity price (e.g. in EUR/kWh), but this field can also be used to optimize against some emission intensity factor (e.g. in kg CO₂ eq./kWh). Follow up with the sensor's ID.",
 )
+@click.option(
+    "--consumption-price-sensor-per-device",
+    "consumption_price_sensor_per_device",
+    type=dict,
+    required=False,
+    # help="Optimize consumption against this sensor. The sensor typically records an electricity price (e.g. in EUR/kWh), but this field can also be used to optimize against some emission intensity factor (e.g. in kg CO₂ eq./kWh). Follow up with the sensor's ID.",
+)
+@click.option(
+    "--production-price-sensor-per-device",
+    "production_price_sensor_per_device",
+    type=dict,
+    required=False,
+    # help="Optimize production against this sensor. Defaults to the consumption price sensor. The sensor typically records an electricity price (e.g. in EUR/kWh), but this field can also be used to optimize against some emission intensity factor (e.g. in kg CO₂ eq./kWh). Follow up with the sensor's ID.",
+)
 @click.option(
     "--optimization-context-id",
     "optimization_context_sensor",
@@ -1023,6 +1037,8 @@ def add_schedule_for_storage(
     production_price_sensor: Sensor,
     optimization_context_sensor: Sensor,
     inflexible_device_sensors: list[Sensor],
+    consumption_price_sensors_per_device: dict(Sensor, Sensor),
+    production_price_sensors_per_device: dict(Sensor, Sensor),
     start: datetime,
     duration: timedelta,
     soc_at_start: ur.Quantity,
@@ -1103,6 +1119,8 @@ def add_schedule_for_storage(
             "consumption-price-sensor": consumption_price_sensor.id,
             "production-price-sensor": production_price_sensor.id,
             "inflexible-device-sensors": [s.id for s in inflexible_device_sensors],
+            "consumption-price-sensors-per-device": {(power.id, price.id) for (power, price) in consumption_price_sensors_per_device.items()},
+            "production-price-sensors-per-device": {(power.id, price.id) for (power, price) in production_price_sensors_per_device.items()},
         },
     )
     if as_job:

flexmeasures/data/models/planning/linear_optimization.py

@@ -29,8 +29,8 @@ def device_scheduler(  # noqa C901
     device_constraints: List[pd.DataFrame],
     ems_constraints: pd.DataFrame,
     commitment_quantities: List[pd.Series],
-    commitment_downwards_deviation_price: Union[List[pd.Series], List[float]],
-    commitment_upwards_deviation_price: Union[List[pd.Series], List[float]],
+    commitment_downwards_deviation_price_array: List[Union[List[pd.Series], List[float]]],
+    commitment_upwards_deviation_price_array: List[Union[List[pd.Series], List[float]]],
 ) -> Tuple[List[pd.Series], float, SolverResults]:
     """This generic device scheduler is able to handle an EMS with multiple devices,
     with various types of constraints on the EMS level and on the device level,

flexmeasures/data/models/planning/storage.py

@@ -48,56 +48,107 @@ def compute_schedule(
         roundtrip_efficiency = self.flex_model.get("roundtrip_efficiency")
         prefer_charging_sooner = self.flex_model.get("prefer_charging_sooner", True)
 
-        consumption_price_sensor = self.flex_context.get("consumption_price_sensor")
-        production_price_sensor = self.flex_context.get("production_price_sensor")
+        # consumption_price_sensor = self.flex_context.get("consumption_price_sensor")
+        # production_price_sensor = self.flex_context.get("production_price_sensor")
         inflexible_device_sensors = self.flex_context.get(
             "inflexible_device_sensors", []
         )
-
+        consumption_price_sensor_per_device = self.flex_context.get("consumption_price_sensor_per_device", {})
+        production_price_sensor_per_device = self.flex_context.get("production_price_sensor_per_device", {})
+
         # Check for required Sensor attributes
         self.sensor.check_required_attributes([("capacity_in_mw", (float, int))])
 
         # Check for known prices or price forecasts, trimming planning window accordingly
-        up_deviation_prices, (start, end) = get_prices(
-            (start, end),
-            resolution,
-            beliefs_before=belief_time,
-            price_sensor=consumption_price_sensor,
-            sensor=sensor,
-            allow_trimmed_query_window=False,
-        )
-        down_deviation_prices, (start, end) = get_prices(
-            (start, end),
-            resolution,
-            beliefs_before=belief_time,
-            price_sensor=production_price_sensor,
-            sensor=sensor,
-            allow_trimmed_query_window=False,
-        )
+        # up_deviation_prices, (start, end) = get_prices(
+        #     (start, end),
+        #     resolution,
+        #     beliefs_before=belief_time,
+        #     price_sensor=consumption_price_sensor,
+        #     sensor=sensor,
+        #     allow_trimmed_query_window=False,
+        # )
+        # down_deviation_prices, (start, end) = get_prices(
+        #     (start, end),
+        #     resolution,
+        #     beliefs_before=belief_time,
+        #     price_sensor=production_price_sensor,
+        #     sensor=sensor,
+        #     allow_trimmed_query_window=False,
+        # )
+
+        up_deviation_prices_array = []
+        for power_sensor, price_sensor in consumption_price_sensor_per_device.items():
+
+            # Check for known prices or price forecasts, trimming planning window accordingly
+            up_deviation_prices, (start, end) = get_prices(
+                (start, end),
+                resolution,
+                beliefs_before=belief_time,
+                price_sensor=price_sensor,
+                sensor=power_sensor,
+                allow_trimmed_query_window=False,
+            )
+            up_deviation_prices_array.append(up_deviation_prices)
+
+        down_deviation_prices_array = []
+        for power_sensor, price_sensor in production_price_sensor_per_device.items():    
+
+            down_deviation_prices, (start, end) = get_prices(
+                (start, end),
+                resolution,
+                beliefs_before=belief_time,
+                price_sensor=price_sensor,
+                sensor=power_sensor,
+                allow_trimmed_query_window=False,
+            )
+            down_deviation_prices_array.append(down_deviation_prices)
 
         start = pd.Timestamp(start).tz_convert("UTC")
         end = pd.Timestamp(end).tz_convert("UTC")
 
         # Add tiny price slope to prefer charging now rather than later, and discharging later rather than now.
         # We penalise the future with at most 1 per thousand times the price spread.
+        # if prefer_charging_sooner:
+        #     up_deviation_prices = add_tiny_price_slope(
+        #         up_deviation_prices, "event_value"
+        #     )
+        #     down_deviation_prices = add_tiny_price_slope(
+        #         down_deviation_prices, "event_value"
+        #     )
         if prefer_charging_sooner:
-            up_deviation_prices = add_tiny_price_slope(
-                up_deviation_prices, "event_value"
-            )
-            down_deviation_prices = add_tiny_price_slope(
-                down_deviation_prices, "event_value"
-            )
-
+            for i in range(0, len(up_deviation_prices_array)):
+                up_deviation_prices[i] = add_tiny_price_slope(
+                    up_deviation_prices[i], "event_value"
+                )
+            for i in range(0, len(down_deviation_prices_array)): 
+                down_deviation_prices[i] = add_tiny_price_slope(
+                    down_deviation_prices[i], "event_value"
+                )        
         # Set up commitments to optimise for
         commitment_quantities = [initialize_series(0, start, end, self.resolution)]
 
         # Todo: convert to EUR/(deviation of commitment, which is in MW)
-        commitment_upwards_deviation_price = [
-            up_deviation_prices.loc[start : end - resolution]["event_value"]
-        ]
-        commitment_downwards_deviation_price = [
-            down_deviation_prices.loc[start : end - resolution]["event_value"]
-        ]
+        # commitment_upwards_deviation_price = [
+        #     up_deviation_prices.loc[start : end - resolution]["event_value"]
+        # ]
+        # commitment_downwards_deviation_price = [
+        #     down_deviation_prices.loc[start : end - resolution]["event_value"]
+        # ]
+
+        commitment_upwards_deviation_price_array = []
+        for up_deviation_price in up_deviation_prices_array:
+            commitment_upwards_deviation_price = [
+                up_deviation_price.loc[start : end - resolution]["event_value"]
+            ]
+            commitment_upwards_deviation_price_array.append(commitment_upwards_deviation_price)
+
+        commitment_downwards_deviation_price_array = []
+        for down_deviation_price in down_deviation_prices_array:    
+            commitment_downwards_deviation_price = [
+                down_deviation_price.loc[start : end - resolution]["event_value"]
+            ]
+            commitment_downwards_deviation_price_array.append(commitment_downwards_deviation_price)
 
         # Set up device constraints: only one scheduled flexible device for this EMS (at index 0), plus the forecasted inflexible devices (at indices 1 to n).
         columns = [
@@ -169,8 +220,8 @@ def compute_schedule(
             device_constraints,
             ems_constraints,
             commitment_quantities,
-            commitment_downwards_deviation_price,
-            commitment_upwards_deviation_price,
+            commitment_downwards_deviation_price_array,
+            commitment_upwards_deviation_price_array,
         )
         if scheduler_results.solver.termination_condition == "infeasible":
             # Fallback policy if the problem was unsolvable

flexmeasures/data/schemas/scheduling/__init__.py

@@ -13,3 +13,9 @@ class FlexContextSchema(Schema):
     inflexible_device_sensors = fields.List(
         SensorIdField(), data_key="inflexible-device-sensors"
     )
+    consumption_price_sensors_per_device = fields.Dict(
+        SensorIdField(), SensorIdField(), data_key="consumption-price-sensors-per-device"
+    )
+    production_price_sensors_per_device = fields.Dict(
+        SensorIdField(), SensorIdField(), data_key="production-price-sensors-per-device"
+    )

flyway/postgres/sql/V0001__.sql

@@ -1011,9 +1011,9 @@ INSERT INTO "public"."roles_users" ("id", "user_id", "role_id") VALUES (1, 1, 1)
 INSERT INTO "public"."sensor" ("id", "name", "unit", "timezone", "event_resolution", "knowledge_horizon_fnc", "knowledge_horizon_par", "generic_asset_id", "attributes") VALUES (13, 'power-1', 'MW', 'Europe/Amsterdam', '00:15:00', 'ex_post', '{"ex_post_horizon": "P0D"}', 1, '{}');
 INSERT INTO "public"."sensor" ("id", "name", "unit", "timezone", "event_resolution", "knowledge_horizon_fnc", "knowledge_horizon_par", "generic_asset_id", "attributes") VALUES (14, 'power-2', 'MW', 'Europe/Amsterdam', '00:15:00', 'ex_post', '{"ex_post_horizon": "P0D"}', 5, '{}');
 INSERT INTO "public"."sensor" ("id", "name", "unit", "timezone", "event_resolution", "knowledge_horizon_fnc", "knowledge_horizon_par", "generic_asset_id", "attributes") VALUES (15, 'power-3', 'MW', 'Europe/Amsterdam', '00:15:00', 'ex_post', '{"ex_post_horizon": "P0D"}', 2, '{}');
-INSERT INTO "public"."sensor" ("id", "name", "unit", "timezone", "event_resolution", "knowledge_horizon_fnc", "knowledge_horizon_par", "generic_asset_id", "attributes") VALUES (11, 'price-solar-1', 'EUR/MWh', 'Europe/Amsterdam', '01:00:00', 'x_days_ago_at_y_oclock', '{"x": 1, "y": 12, "z": "Europe/Paris"}',1, '{}');
+INSERT INTO "public"."sensor" ("id", "name", "unit", "timezone", "event_resolution", "knowledge_horizon_fnc", "knowledge_horizon_par", "generic_asset_id", "attributes") VALUES (9, 'price-solar-1', 'EUR/MWh', 'Europe/Amsterdam', '01:00:00', 'x_days_ago_at_y_oclock', '{"x": 1, "y": 12, "z": "Europe/Paris"}',1, '{}');
 INSERT INTO "public"."sensor" ("id", "name", "unit", "timezone", "event_resolution", "knowledge_horizon_fnc", "knowledge_horizon_par", "generic_asset_id", "attributes") VALUES (10, 'price-solar-2', 'EUR/MWh', 'Europe/Amsterdam', '01:00:00', 'x_days_ago_at_y_oclock', '{"x": 1, "y": 12, "z": "Europe/Paris"}', 5, '{}');
-INSERT INTO "public"."sensor" ("id", "name", "unit", "timezone", "event_resolution", "knowledge_horizon_fnc", "knowledge_horizon_par", "generic_asset_id", "attributes") VALUES (9, 'battery-cprice', 'EUR/MWh', 'Europe/Amsterdam', '01:00:00', 'x_days_ago_at_y_oclock', '{"x": 1, "y": 12, "z": "Europe/Paris"}', 3, '{}');
+INSERT INTO "public"."sensor" ("id", "name", "unit", "timezone", "event_resolution", "knowledge_horizon_fnc", "knowledge_horizon_par", "generic_asset_id", "attributes") VALUES (11, 'battery-cprice', 'EUR/MWh', 'Europe/Amsterdam', '01:00:00', 'x_days_ago_at_y_oclock', '{"x": 1, "y": 12, "z": "Europe/Paris"}', 3, '{}');
 
 
 --