various improvements for pypsa and amiris loader

assume/common/forecasts.py

@@ -552,6 +552,13 @@ def __init__(
             index=self.index, value=price_forecast, name="price_forecast"
         )
 
+        self.data_dict = {}
+
+        for key, value in kwargs.items():
+            self.data_dict[key] = FastSeries(index=self.index, value=value, name=key)
+
+
+
     def __getitem__(self, column: str) -> FastSeries:
         """
         Retrieves forecasted values.
@@ -579,5 +586,7 @@ def __getitem__(self, column: str) -> FastSeries:
             return self.demand
         elif column == "price_EOM":
             return self.price_forecast
+        elif column in self.data_dict.keys():
+            return self.data_dict[column]
         else:
             return FastSeries(value=0.0, index=self.index)

assume/common/grid_utils.py

@@ -38,9 +38,9 @@ def add_generators(
         if "marginal_cost" not in gen_c.columns:
             gen_c["marginal_cost"] = p_set
 
-        network.madd(
+        network.add(
             "Generator",
-            names=generators.index,
+            name=generators.index,
             bus=generators["node"],  # bus to which the generator is connected to
             p_nom=generators[
                 "max_power"
@@ -49,16 +49,17 @@ def add_generators(
         )
     else:
         # add generators
-        network.madd(
+        #generators.drop(["p_min_pu", "p_max_pu", "marginal_cost"], axis=1, inplace=True)7
+        #generators["p_min_pu"] = p_set
+        #generators["p_max_pu"] = p_set + 1
+        #generators["marginal_cost"] = p_set
+        network.add(
             "Generator",
-            names=generators.index,
+            name=generators.index,
             bus=generators["node"],  # bus to which the generator is connected to
             p_nom=generators[
                 "max_power"
             ],  # Nominal capacity of the powerplant/generator
-            p_min_pu=p_set,
-            p_max_pu=p_set + 1,
-            marginal_cost=p_set,
             **generators,
         )
 
@@ -84,18 +85,18 @@ def add_redispatch_generators(
     )
 
     # add generators and their sold capacities as load with reversed sign to have fixed feed in
-    network.madd(
+    network.add(
         "Load",
-        names=generators.index,
+        name=generators.index,
         bus=generators["node"],  # bus to which the generator is connected to
         p_set=p_set,
         sign=1,
     )
 
     # add upward redispatch generators
-    network.madd(
+    network.add(
         "Generator",
-        names=generators.index,
+        name=generators.index,
         suffix="_up",
         bus=generators["node"],  # bus to which the generator is connected to
         p_nom=generators["max_power"],  # Nominal capacity of the powerplant/generator
@@ -105,9 +106,9 @@ def add_redispatch_generators(
     )
 
     # add downward redispatch generators
-    network.madd(
+    network.add(
         "Generator",
-        names=generators.index,
+        name=generators.index,
         suffix="_down",
         bus=generators["node"],  # bus to which the generator is connected to
         p_nom=generators["max_power"],  # Nominal capacity of the powerplant/generator
@@ -118,18 +119,18 @@ def add_redispatch_generators(
     )
 
     # add upward and downward backup generators at each node
-    network.madd(
+    network.add(
         "Generator",
-        names=network.buses.index,
+        name=network.buses.index,
         suffix="_backup_up",
         bus=network.buses.index,  # bus to which the generator is connected to
         p_nom=10e4,
         marginal_cost=backup_marginal_cost,
     )
 
-    network.madd(
+    network.add(
         "Generator",
-        names=network.buses.index,
+        name=network.buses.index,
         suffix="_backup_down",
         bus=network.buses.index,  # bus to which the generator is connected to
         p_nom=10e4,
@@ -151,9 +152,9 @@ def add_backup_generators(
     """
 
     # add backup generators at each node
-    network.madd(
+    network.add(
         "Generator",
-        names=network.buses.index,
+        name=network.buses.index,
         suffix="_backup",
         bus=network.buses.index,  # bus to which the generator is connected to
         p_nom=10e4,
@@ -174,9 +175,9 @@ def add_loads(
     """
 
     # add loads
-    network.madd(
+    network.add(
         "Load",
-        names=loads.index,
+        name=loads.index,
         bus=loads["node"],  # bus to which the generator is connected to
         **loads,
     )
@@ -201,9 +202,9 @@ def add_redispatch_loads(
         del loads_c["sign"]
 
     # add loads with opposite sign (default for loads is -1). This is needed to properly model the redispatch
-    network.madd(
+    network.add(
         "Load",
-        names=loads.index,
+        name=loads.index,
         bus=loads["node"],  # bus to which the generator is connected to
         sign=1,
         **loads_c,
@@ -237,9 +238,9 @@ def add_nodal_loads(
         del loads_c["sign"]
 
     # add loads as negative generators
-    network.madd(
+    network.add(
         "Generator",
-        names=loads.index,
+        name=loads.index,
         bus=loads["node"],  # bus to which the generator is connected to
         p_nom=loads["max_power"],  # Nominal capacity of the powerplant/generator
         p_min_pu=p_set,
@@ -264,10 +265,10 @@ def read_pypsa_grid(
     """
 
     def add_buses(network: pypsa.Network, buses: pd.DataFrame) -> None:
-        network.import_components_from_dataframe(buses, "Bus")
+        network.add("Bus", buses.index, **buses)
 
     def add_lines(network: pypsa.Network, lines: pd.DataFrame) -> None:
-        network.import_components_from_dataframe(lines, "Line")
+        network.add("Line", lines.index, **lines)
 
     # setup the network
     add_buses(network, grid_dict["buses"])

assume/markets/clearing_algorithms/nodal_pricing.py

@@ -264,4 +264,4 @@ def process_dispatch_data(
                 # rename columns
                 flows.columns = ["datetime", "line", "flow"]
 
-        return flows
+        return flows.to_dict(orient="records")

assume/markets/clearing_algorithms/redispatch.py

@@ -225,7 +225,7 @@ def clear(
                 calculate_network_meta(network=redispatch_network, product=product, i=i)
             )
 
-        # write network flows here if applicable
+        # TODO write network flows here
         flows = []
 
         return accepted_orders, rejected_orders, meta, flows

assume/scenario/loader_amiris.py

@@ -254,7 +254,8 @@ def add_agent_to_world(
                         "technology": "demand",
                         "price": load["ValueOfLostLoad"],
                     },
-                    NaiveForecast(index, demand=demand_series),
+                    # demand_series might contain more values than index
+                    NaiveForecast(index, demand=demand_series[:len(index)]),
                 )
 
         case "StorageTrader":

assume/scenario/loader_pypsa.py

@@ -118,8 +118,10 @@ def load_pypsa(
         load_t = network.loads_t["p_set"][load.name]
         unit_type = "demand"
 
+        kwargs = {load.name: load_t}
+
         world.add_unit(
-            f"demand_{load.name}",
+            load.name,
             unit_type,
             "demand_operator",
             {
@@ -130,7 +132,7 @@ def load_pypsa(
                 "node": load.node,
                 "price": 1e3,
             },
-            NaiveForecast(index, demand=load_t),
+            NaiveForecast(index, demand=load_t, **kwargs),
         )
 
     world.add_unit_operator("storage_operator")
@@ -171,7 +173,7 @@ def load_pypsa(
     scenario = "world_pypsa"
     study_case = "scigrid_de"
     # "pay_as_clear", "redispatch" or "nodal"
-    market_mechanism = "nodal"
+    market_mechanism = "pay_as_clear"
 
     match study_case:
         case "ac_dc_meshed":
@@ -184,7 +186,7 @@ def load_pypsa(
             logger.info(f"invalid studycase: {study_case}")
             network = pd.DataFrame()
 
-    study_case += market_mechanism
+    study_case = f"{study_case}_{market_mechanism}" 
 
     start = network.snapshots[0]
     end = network.snapshots[-1]

assume/units/powerplant.py

@@ -273,13 +273,13 @@ def calculate_min_max_power(
         min_power = min_power.clip(min=heat_demand)
 
         available_power = self.forecaster.get_availability(self.id).loc[start:end_excl]
+        max_power = available_power * self.max_power
         # check if available power is larger than max_power and raise an error if so
-        if (available_power > self.max_power).any():
+        if (max_power > self.max_power).any():
             raise ValueError(
                 f"Available power is larger than max_power for unit {self.id} at time {start}."
             )
 
-        max_power = available_power * self.max_power
         # provide reserve for capacity_pos
         max_power = max_power - self.outputs["capacity_pos"].loc[start:end_excl]
         # remove what has already been bid

docker_configs/mqtt.conf

@@ -3,6 +3,7 @@
 # SPDX-License-Identifier: AGPL-3.0-or-later
 # https://github.com/eclipse/mosquitto/blob/master/mosquitto.conf
 listener 1883
+set_tcp_nodelay true
 allow_anonymous true
 
 max_keepalive 3600