various review comments

Signed-off-by: Nicolas Höning <nicolas@seita.nl>

documentation/plugin/customisation.rst

@@ -33,9 +33,13 @@ The following minimal example gives you an idea of the inputs and outputs:
         *args,
         **kwargs
     ):
-        """Just a dummy scheduler, advising to do nothing"""
+        """
+        Just a dummy scheduler that always plans to consume at maximum capacity.
+        (Schedulers return positive values for consumption, and negative values for production)
+        """
         return pd.Series(
-            0, index=pd.date_range(start, end, freq=resolution, closed="left")
+            sensor.get_attribute("capacity_in_mw"),
+            index=pd.date_range(start, end, freq=resolution, closed="left"),
         )
 
 

flexmeasures/api/v3_0/sensors.py

@@ -256,20 +256,21 @@ def trigger_schedule(  # noqa: C901
         .. :quickref: Schedule; Trigger scheduling job
 
         Trigger FlexMeasures to create a schedule for this sensor.
-        The assumption is that this sensor is the energy sensor on a flexible asset.
+        The assumption is that this sensor is the power sensor on a flexible asset.
 
         In this request, you can describe:
 
         - the schedule (start, unit, prior)
         - the flexibility model for the sensor (see below, only storage models are supported at the moment)
-        - the EMS the sensor operates in (inflexible device sensors, sensors which put a price on consumption and/or production)
+        - the EMS the sensor operates in (inflexible device sensors, and sensors that put a price on consumption and/or production)
 
-        Note: This endpoint does not support an EMS with multiple flexible sensors. This will happen in another endpoint.
-              See https://github.com/FlexMeasures/flexmeasures/issues/485
+        Note: This endpoint does not support to schedule an EMS with multiple flexible sensors at once. This will happen in another endpoint.
+              See https://github.com/FlexMeasures/flexmeasures/issues/485. Until then, it is possible to call this endpoint for one flexible endpoint at a time
+              (considering already scheduled sensors as inflexible).
 
         Flexibility models apply to the sensor's asset type:
 
-        1) For storage sensors (e.g. battery, charging stations), the schedule deals with the state of charge (SOC).
+        1) For storage sensors (e.g. battery, charge points), the schedule deals with the state of charge (SOC).
            The possible flexibility parameters are:
 
             - soc-at-start (defaults to 0)
@@ -365,7 +366,7 @@ def trigger_schedule(  # noqa: C901
         if unit == "kWh":
             start_value = start_value / 1000.0
 
-        # Convert round-trip efficiency to dimensionless (to the [0,1] range)
+        # Convert round-trip efficiency to dimensionless (to the (0,1] range)
         if roundtrip_efficiency is not None:
             roundtrip_efficiency = roundtrip_efficiency.to(
                 ur.Quantity("dimensionless")

flexmeasures/data/models/planning/utils.py

@@ -17,9 +17,15 @@
 
 
 def initialize_df(
-    columns: List[str], start: datetime, end: datetime, resolution: timedelta
+    columns: List[str],
+    start: datetime,
+    end: datetime,
+    resolution: timedelta,
+    inclusive: str,
 ) -> pd.DataFrame:
-    df = pd.DataFrame(index=initialize_index(start, end, resolution), columns=columns)
+    df = pd.DataFrame(
+        index=initialize_index(start, end, resolution, inclusive), columns=columns
+    )
     return df
 
 
@@ -28,16 +34,25 @@ def initialize_series(
     start: datetime,
     end: datetime,
     resolution: timedelta,
+    inclusive: str,
 ) -> pd.Series:
-    s = pd.Series(index=initialize_index(start, end, resolution), data=data)
+    s = pd.Series(index=initialize_index(start, end, resolution, inclusive), data=data)
     return s
 
 
 def initialize_index(
-    start: Union[date, datetime], end: Union[date, datetime], resolution: timedelta
+    start: Union[date, datetime],
+    end: Union[date, datetime],
+    resolution: timedelta,
+    inclusive: str = "left",
 ) -> pd.DatetimeIndex:
+    assert inclusive == "left" or inclusive == "right"
     i = pd.date_range(
-        start=start, end=end, freq=to_offset(resolution), closed="left", name="datetime"
+        start=start,
+        end=end,
+        freq=to_offset(resolution),
+        closed=inclusive,
+        name="datetime",
     )
     return i
 
@@ -101,7 +116,7 @@ def ensure_sensor_is_set(sensor) -> Sensor:
     # Check for min and max SOC, or get default from sensor
     if "soc_min" not in specs or specs["soc_min"] is None:
         sensor = ensure_sensor_is_set(sensor)
-        # Can't drain the EV battery by more than it contains
+        # Can't drain the storage by more than it contains
         specs["soc_min"] = sensor.get_attribute("min_soc_in_mwh", 0)
     if "soc_max" not in specs or specs["soc_max"] is None:
         sensor = ensure_sensor_is_set(sensor)
@@ -234,6 +249,10 @@ def get_power_values(
         raise UnknownForecastException(
             f"Forecasts unknown for planning window. (sensor {sensor.id})"
         )
+    if sensor.get_attribute(
+        "consumption_is_positive", False
+    ):  # FlexMeasures default is to store consumption as negative power values
+        return df.values
     return -df.values
 
 

flexmeasures/data/services/scheduling.py

@@ -109,7 +109,7 @@ def make_schedule(
 
     - Choose which scheduling function can be used
     - Compute schedule
-    - Turn schedukled values into beliefs and save them to db
+    - Turn scheduled values into beliefs and save them to db
     """
     # https://docs.sqlalchemy.org/en/13/faq/connections.html#how-do-i-use-engines-connections-sessions-with-python-multiprocessing-or-os-fork
     db.engine.dispose()
@@ -202,7 +202,7 @@ def load_custom_scheduler(scheduler_specs: dict) -> Tuple[Callable, str]:
     assert "function" in scheduler_specs, "scheduler specs have no 'function'"
 
     source_name = scheduler_specs.get(
-        "source", f"Custom scheduler - {scheduler_specs['function']}"
+        "source", f"custom scheduler - {scheduler_specs['function']}"
     )
     scheduler_name = scheduler_specs["function"]
 

flexmeasures/data/tests/dummy_scheduler.py

@@ -12,10 +12,13 @@ def compute_a_schedule(
     *args,
     **kwargs
 ):
-    """Just a dummy scheduler."""
+    """
+    Just a dummy scheduler that always plans to consume at maximum capacity.
+    (Schedulers return positive values for consumption, and negative values for production)
+    """
     return initialize_series(  # simply creates a Pandas Series repeating one value
         data=sensor.get_attribute("capacity_in_mw"),
         start=start,
         end=end,
         resolution=resolution,
-    )
+    )