Merge pull request #43 from Open-ISP/multi-investment-periods

Multi period investment

Author: nick-gorman

dodo.py

@@ -127,7 +127,7 @@ def create_pypsa_inputs_from_config_and_ispypsa_inputs(
         regional_granularity=config.network.nodes.regional_granularity,
         reference_year_mapping=reference_year_mapping,
         year_type=config.temporal.year_type,
-        snapshot=pypsa_tables["snapshots"],
+        snapshots=pypsa_tables["snapshots"],
     )
 
 

example_workflow.py

@@ -77,7 +77,7 @@
     regional_granularity=config.network.nodes.regional_granularity,
     reference_year_mapping=reference_year_mapping,
     year_type=config.temporal.year_type,
-    snapshot=pypsa_friendly_input_tables["snapshots"],
+    snapshots=pypsa_friendly_input_tables["snapshots"],
 )
 
 # Build a PyPSA network object.

ispypsa_runs/development/ispypsa_inputs/ispypsa_config.yaml

@@ -12,6 +12,8 @@ scenario: Step Change
 # Weighted average cost of capital for annuitisation of generation and transmission
 # costs, as a fraction, i.e. 0.07 is 7%.
 wacc: 0.07
+# Discount rate applied to model objective function, as a fraction, i.e. 0.07 is 7%.
+discount_rate: 0.05
 network:
   # Does the model consider the expansion of sub-region to sub-region transmission
   # capacity
@@ -44,8 +46,11 @@ temporal:
   path_to_parsed_traces: ENV
   year_type: fy
   start_year: 2025
-  end_year: 2025
+  end_year: 2028
   reference_year_cycle: [2018]
+  # List of investment period start years. An investment period runs until the next the
+  # periods begins.
+  investment_periods: [2025, 2026]
   aggregation:
     # Representative weeks to use instead of full yearly temporal representation.
     # Options:

src/ispypsa/config/validators.py

@@ -31,6 +31,7 @@ class TemporalConfig(BaseModel):
     start_year: int
     end_year: int
     reference_year_cycle: list[int]
+    investment_periods: list[int]
     aggregation: TemporalAggregationConfig
 
     @field_validator("operational_temporal_resolution_min")
@@ -86,11 +87,27 @@ def validate_end_year(cls, end_year: float, info):
             )
         return end_year
 
+    @field_validator("investment_periods")
+    @classmethod
+    def validate_investment_periods(cls, investment_periods: float, info):
+        if min(investment_periods) != info.data.get("start_year"):
+            raise ValueError(
+                "config first investment period must be equal to start_year"
+            )
+        if len(investment_periods) != len(set(investment_periods)):
+            raise ValueError("config all years in investment_periods must be unique")
+        if sorted(investment_periods) != investment_periods:
+            raise ValueError(
+                "config investment_periods must be provided in sequential order"
+            )
+        return investment_periods
+
 
 class ModelConfig(BaseModel):
     ispypsa_run_name: str
     scenario: Literal[tuple(_ISP_SCENARIOS)]
     wacc: float
+    discount_rate: float
     network: NetworkConfig
     temporal: TemporalConfig
     iasr_workbook_version: str

src/ispypsa/model/build.py

@@ -10,6 +10,7 @@
     _add_generators_to_network,
 )
 from ispypsa.model.initialise import _initialise_network
+from ispypsa.model.investment_period_weights import _add_investment_period_weights
 from ispypsa.model.lines import _add_lines_to_network
 
 
@@ -49,6 +50,10 @@ def build_pypsa_network(
     """
     network = _initialise_network(pypsa_friendly_tables["snapshots"])
 
+    _add_investment_period_weights(
+        network, pypsa_friendly_tables["investment_period_weights"]
+    )
+
     _add_carriers_to_network(network, pypsa_friendly_tables["generators"])
 
     _add_buses_to_network(

src/ispypsa/model/buses.py

@@ -24,12 +24,12 @@ def _add_bus_to_network(
     demand_trace_path = path_to_demand_traces / Path(f"{bus_name}.parquet")
     if demand_trace_path.exists():
         demand = pd.read_parquet(demand_trace_path)
-        demand = demand.set_index("Datetime")
+        demand = demand.set_index(["investment_periods", "snapshots"])
         network.add(
             class_name="Load",
             name=f"load_{bus_name}",
             bus=bus_name,
-            p_set=demand["Value"],
+            p_set=demand["p_set"],
         )
 
 

src/ispypsa/model/generators.py

@@ -51,7 +51,8 @@ def _add_generator_to_network(
         trace_data = None
 
     if trace_data is not None:
-        generator_definition["p_max_pu"] = trace_data.set_index("Datetime")["Value"]
+        trace_data = trace_data.set_index(["investment_periods", "snapshots"])
+        generator_definition["p_max_pu"] = trace_data["p_max_pu"]
 
     network.add(**generator_definition)
 

src/ispypsa/model/initialise.py

@@ -12,6 +12,12 @@ def _initialise_network(snapshots: pd.DataFrame) -> pypsa.Network:
     Returns:
         `pypsa.Network` object
     """
-    snapshots = pd.to_datetime(snapshots["snapshots"])
-    network = pypsa.Network(snapshots=snapshots)
+    snapshots["snapshots"] = pd.to_datetime(snapshots["snapshots"])
+    snapshots_as_indexes = pd.MultiIndex.from_arrays(
+        [snapshots["investment_periods"], snapshots["snapshots"]]
+    )
+    network = pypsa.Network(
+        snapshots=snapshots_as_indexes,
+        investment_periods=snapshots["investment_periods"].unique(),
+    )
     return network

src/ispypsa/model/investment_period_weights.py

@@ -0,0 +1,21 @@
+import pandas as pd
+import pypsa
+
+
+def _add_investment_period_weights(
+    network: pypsa.Network, investment_period_weights: pd.DataFrame
+) -> None:
+    """Adds investment period weights defined in a pypsa-friendly `pd.DataFrame` to the `pypsa.Network`.
+
+    Args:
+        network: The `pypsa.Network` object
+        investment_period_weights: `pd.DataFrame` specifying the
+            investment period weights with columns 'period', "years" and 'objective'.
+            Where "period" is the start years of the investment periods, "years" is the
+            length of each investment period, and "objective" is the relative weight of
+            the objective function in each investment period.
+
+    Returns: None
+    """
+    investment_period_weights = investment_period_weights.set_index("period")
+    network.investment_period_weightings = investment_period_weights

src/ispypsa/templater/nodes.py

@@ -197,13 +197,9 @@ def _request_transmission_substation_coordinates() -> pd.DataFrame:
             data = xmltodict.parse(r.content)
             features = data["wfs:FeatureCollection"]["wfs:member"]
             for feature in features:
-                substation = feature[
-                    "Foundation_Electricity_Infrastructure:Transmission_Substations"
-                ]
-                name = substation.get("Foundation_Electricity_Infrastructure:NAME")
-                coordinates = substation["Foundation_Electricity_Infrastructure:SHAPE"][
-                    "gml:Point"
-                ]["gml:pos"]
+                substation = feature["esri:Transmission_Substations"]
+                name = substation.get("esri:NAME")
+                coordinates = substation["esri:SHAPE"]["gml:Point"]["gml:pos"]
                 lat, long = coordinates.split(" ")
                 substation_coordinates[name] = {
                     "substation_latitude": lat,

src/ispypsa/translator/buses.py

@@ -70,7 +70,7 @@ def create_pypsa_friendly_bus_demand_timeseries(
     regional_granularity: str,
     reference_year_mapping: dict[int:int],
     year_type: Literal["fy", "calendar"],
-    snapshot: pd.DataFrame,
+    snapshots: pd.DataFrame,
 ) -> None:
     """Gets trace data for operational demand by constructing a timeseries from the
     start to end year using the reference year cycle provided.
@@ -93,7 +93,7 @@ def create_pypsa_friendly_bus_demand_timeseries(
             year with start_year and end_year specifiying the financial year to return
             data for, using year ending nomenclature (2016 ->FY2015/2016). If
             'calendar', then filtering is by calendar year.
-        snapshot: pd.DataFrame containing the expected time series values.
+        snapshots: pd.DataFrame containing the expected time series values.
 
     Returns:
         None
@@ -134,13 +134,18 @@ def create_pypsa_friendly_bus_demand_timeseries(
         node_trace = node_traces.groupby("Datetime", as_index=False)["Value"].sum()
         # datetime in nanoseconds required by PyPSA
         node_trace["Datetime"] = node_trace["Datetime"].astype("datetime64[ns]")
-        node_trace = _time_series_filter(node_trace, snapshot)
+        node_trace = node_trace.rename(
+            columns={"Datetime": "snapshots", "Value": "p_set"}
+        )
+        node_trace = _time_series_filter(node_trace, snapshots)
         _check_time_series(
-            node_trace["Datetime"],
-            snapshot["snapshots"],
+            node_trace["snapshots"],
+            snapshots["snapshots"],
             "demand data",
             demand_node,
         )
+        node_trace = pd.merge(node_trace, snapshots, on="snapshots")
+        node_trace = node_trace.loc[:, ["investment_periods", "snapshots", "p_set"]]
         node_trace.to_parquet(
             Path(output_trace_path, f"{demand_node}.parquet"), index=False
         )

src/ispypsa/translator/create_pypsa_friendly_inputs.py

@@ -26,11 +26,16 @@
 from ispypsa.translator.renewable_energy_zones import (
     _translate_renewable_energy_zone_build_limits_to_flow_paths,
 )
-from ispypsa.translator.snapshot import _create_complete_snapshots_index
+from ispypsa.translator.snapshots import (
+    _add_investment_periods,
+    _create_complete_snapshots_index,
+    _create_investment_period_weightings,
+)
 from ispypsa.translator.temporal_filters import _filter_snapshots
 
 _BASE_TRANSLATOR_OUPUTS = [
     "snapshots",
+    "investment_period_weights",
     "buses",
     "lines",
     "generators",
@@ -83,8 +88,16 @@ def create_pypsa_friendly_inputs(
         year_type=config.temporal.year_type,
     )
 
-    pypsa_inputs["snapshots"] = _filter_snapshots(
-        config=config.temporal, snapshots=snapshots
+    snapshots = _filter_snapshots(config=config.temporal, snapshots=snapshots)
+
+    pypsa_inputs["snapshots"] = _add_investment_periods(
+        snapshots, config.temporal.investment_periods, config.temporal.year_type
+    )
+
+    pypsa_inputs["investment_period_weights"] = _create_investment_period_weightings(
+        config.temporal.investment_periods,
+        config.temporal.end_year,
+        config.discount_rate,
     )
 
     pypsa_inputs["generators"] = _translate_ecaa_generators(

src/ispypsa/translator/generators.py

@@ -128,8 +128,11 @@ def create_pypsa_friendly_existing_generator_timeseries(
         )
         # datetime in nanoseconds required by PyPSA
         trace["Datetime"] = trace["Datetime"].astype("datetime64[ns]")
+        trace = trace.rename(columns={"Datetime": "snapshots", "Value": "p_max_pu"})
         trace = _time_series_filter(trace, snapshots)
         _check_time_series(
-            trace["Datetime"], snapshots["snapshots"], "generator trace data", gen
+            trace["snapshots"], snapshots["snapshots"], "generator trace data", gen
         )
+        trace = pd.merge(trace, snapshots, on="snapshots")
+        trace = trace.loc[:, ["investment_periods", "snapshots", "p_max_pu"]]
         trace.to_parquet(Path(output_paths[gen_type], f"{gen}.parquet"), index=False)