Merge pull request #912 from PyPSA/fneum/year-specific-techs

 REVIEWED: Add technology specific renewable profiles for different planning horizons

doc/configtables/offwind-ac.csv

@@ -2,7 +2,7 @@
 cutout,--,"Should be a folder listed in the configuration ``atlite: cutouts:`` (e.g. 'europe-2013-era5') or reference an existing folder in the directory ``cutouts``. Source module must be ERA5.","Specifies the directory where the relevant weather data ist stored."
 resource,,,
 -- method,--,"Must be 'wind'","A superordinate technology type."
--- turbine,--,"One of turbine types included in `atlite <https://github.com/PyPSA/atlite/tree/master/atlite/resources/windturbine>`_","Specifies the turbine type and its characteristic power curve."
+-- turbine,--,"One of turbine types included in `atlite <https://github.com/PyPSA/atlite/tree/master/atlite/resources/windturbine>`_.  Can be a string or a dictionary with years as keys which denote the year another turbine model becomes available.","Specifies the turbine type and its characteristic power curve."
 capacity_per_sqkm,:math:`MW/km^2`,float,"Allowable density of wind turbine placement."
 correction_factor,--,float,"Correction factor for capacity factor time series."
 excluder_resolution,m,float,"Resolution on which to perform geographical elibility analysis."

doc/configtables/offwind-dc.csv

@@ -2,7 +2,7 @@
 cutout,--,"Should be a folder listed in the configuration ``atlite: cutouts:`` (e.g. 'europe-2013-era5') or reference an existing folder in the directory ``cutouts``. Source module must be ERA5.","Specifies the directory where the relevant weather data ist stored."
 resource,,,
 -- method,--,"Must be 'wind'","A superordinate technology type."
--- turbine,--,"One of turbine types included in `atlite <https://github.com/PyPSA/atlite/tree/master/atlite/resources/windturbine>`__","Specifies the turbine type and its characteristic power curve."
+-- turbine,--,"One of turbine types included in `atlite <https://github.com/PyPSA/atlite/tree/master/atlite/resources/windturbine>`_. Can be a string or a dictionary with years as keys which denote the year another turbine model becomes available.","Specifies the turbine type and its characteristic power curve."
 capacity_per_sqkm,:math:`MW/km^2`,float,"Allowable density of wind turbine placement."
 correction_factor,--,float,"Correction factor for capacity factor time series."
 excluder_resolution,m,float,"Resolution on which to perform geographical elibility analysis."

doc/configtables/onwind.csv

@@ -2,7 +2,7 @@
 cutout,--,"Should be a folder listed in the configuration ``atlite: cutouts:`` (e.g. 'europe-2013-era5') or reference an existing folder in the directory ``cutouts``. Source module must be ERA5.","Specifies the directory where the relevant weather data ist stored."
 resource,,,
 -- method,--,"Must be 'wind'","A superordinate technology type."
--- turbine,--,"One of turbine types included in `atlite <https://github.com/PyPSA/atlite/tree/master/atlite/resources/windturbine>`__","Specifies the turbine type and its characteristic power curve."
+-- turbine,--,"One of turbine types included in `atlite <https://github.com/PyPSA/atlite/tree/master/atlite/resources/windturbine>`_. Can be a string or a dictionary with years as keys which denote the year another turbine model becomes available.","Specifies the turbine type and its characteristic power curve."
 capacity_per_sqkm,:math:`MW/km^2`,float,"Allowable density of wind turbine placement."
 corine,,,
 -- grid_codes,--,"Any subset of the `CORINE Land Cover code list <http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-1/corine-land-cover-classes-and/clc_legend.csv/at_download/file>`_","Specifies areas according to CORINE Land Cover codes which are generally eligible for wind turbine placement."

doc/configtables/solar.csv

@@ -2,7 +2,7 @@
 cutout,--,"Should be a folder listed in the configuration ``atlite: cutouts:`` (e.g. 'europe-2013-era5') or reference an existing folder in the directory ``cutouts``. Source module can be ERA5 or SARAH-2.","Specifies the directory where the relevant weather data ist stored that is specified at ``atlite/cutouts`` configuration. Both ``sarah`` and ``era5`` work."
 resource,,,
 -- method,--,"Must be 'pv'","A superordinate technology type."
--- panel,--,"One of {'Csi', 'CdTe', 'KANENA'} as defined in `atlite <https://github.com/PyPSA/atlite/tree/master/atlite/resources/solarpanel>`__","Specifies the solar panel technology and its characteristic attributes."
+-- panel,--,"One of {'Csi', 'CdTe', 'KANENA'} as defined in `atlite <https://github.com/PyPSA/atlite/tree/master/atlite/resources/solarpanel>`_ . Can be a string or a dictionary with years as keys which denote the year another turbine model becomes available.","Specifies the solar panel technology and its characteristic attributes."
 -- orientation,,,
 -- -- slope,°,"Realistically any angle in [0., 90.]","Specifies the tilt angle (or slope) of the solar panel. A slope of zero corresponds to the face of the panel aiming directly overhead. A positive tilt angle steers the panel towards the equator."
 -- -- azimuth,°,"Any angle in [0., 360.]","Specifies the `azimuth <https://en.wikipedia.org/wiki/Azimuth>`_ orientation of the solar panel. South corresponds to 180.°."

doc/release_notes.rst

@@ -79,6 +79,12 @@ Upcoming Release
   Energiewende (2021)
   <https://static.agora-energiewende.de/fileadmin/Projekte/2021/2021_02_EU_CEAP/A-EW_254_Mobilising-circular-economy_study_WEB.pdf>`_.
 
+* Added option to specify turbine and solar panel models for specific years as a
+  dictionary (e.g. ``renewable: onwind: resource: turbine:``). The years will be
+  interpreted as years from when the the corresponding turbine model substitutes
+  the previous model for new installations. This will only have an effect on
+  workflows with foresight "myopic" and still needs to be added foresight option
+  "perfect".
 
 
 PyPSA-Eur 0.9.0 (5th January 2024)

rules/solve_myopic.smk

@@ -51,7 +51,16 @@ rule add_brownfield:
         H2_retrofit=config["sector"]["H2_retrofit"],
         H2_retrofit_capacity_per_CH4=config["sector"]["H2_retrofit_capacity_per_CH4"],
         threshold_capacity=config["existing_capacities"]["threshold_capacity"],
+        snapshots={k: config["snapshots"][k] for k in ["start", "end", "inclusive"]},
+        carriers=config["electricity"]["renewable_carriers"],
     input:
+        **{
+            f"profile_{tech}": RESOURCES + f"profile_{tech}.nc"
+            for tech in config["electricity"]["renewable_carriers"]
+            if tech != "hydro"
+        },
+        simplify_busmap=RESOURCES + "busmap_elec_s{simpl}.csv",
+        cluster_busmap=RESOURCES + "busmap_elec_s{simpl}_{clusters}.csv",
         network=RESULTS
         + "prenetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
         network_p=solved_previous_horizon,  #solved network at previous time step

scripts/add_brownfield.py

@@ -11,8 +11,10 @@
 import numpy as np
 import pandas as pd
 import pypsa
+import xarray as xr
 from _helpers import update_config_with_sector_opts
 from add_existing_baseyear import add_build_year_to_new_assets
+from pypsa.clustering.spatial import normed_or_uniform
 
 logger = logging.getLogger(__name__)
 idx = pd.IndexSlice
@@ -143,6 +145,57 @@ def disable_grid_expansion_if_LV_limit_hit(n):
         n.global_constraints.drop("lv_limit", inplace=True)
 
 
+def adjust_renewable_profiles(n, input_profiles, params, year):
+    """
+    Adjusts renewable profiles according to the renewable technology specified,
+    using the latest year below or equal to the selected year.
+    """
+
+    # spatial clustering
+    cluster_busmap = pd.read_csv(snakemake.input.cluster_busmap, index_col=0).squeeze()
+    simplify_busmap = pd.read_csv(
+        snakemake.input.simplify_busmap, index_col=0
+    ).squeeze()
+    clustermaps = simplify_busmap.map(cluster_busmap)
+    clustermaps.index = clustermaps.index.astype(str)
+
+    # temporal clustering
+    dr = pd.date_range(**params["snapshots"], freq="h")
+    snapshotmaps = (
+        pd.Series(dr, index=dr).where(lambda x: x.isin(n.snapshots), pd.NA).ffill()
+    )
+
+    for carrier in params["carriers"]:
+        if carrier == "hydro":
+            continue
+        with xr.open_dataset(getattr(input_profiles, "profile_" + carrier)) as ds:
+            if ds.indexes["bus"].empty or "year" not in ds.indexes:
+                continue
+
+            closest_year = max(
+                (y for y in ds.year.values if y <= year), default=min(ds.year.values)
+            )
+
+            p_max_pu = (
+                ds["profile"]
+                .sel(year=closest_year)
+                .transpose("time", "bus")
+                .to_pandas()
+            )
+
+            # spatial clustering
+            weight = ds["weight"].sel(year=closest_year).to_pandas()
+            weight = weight.groupby(clustermaps).transform(normed_or_uniform)
+            p_max_pu = (p_max_pu * weight).T.groupby(clustermaps).sum().T
+            p_max_pu.columns = p_max_pu.columns + f" {carrier}"
+
+            # temporal_clustering
+            p_max_pu = p_max_pu.groupby(snapshotmaps).mean()
+
+            # replace renewable time series
+            n.generators_t.p_max_pu.loc[:, p_max_pu.columns] = p_max_pu
+
+
 if __name__ == "__main__":
     if "snakemake" not in globals():
         from _helpers import mock_snakemake
@@ -167,6 +220,8 @@ def disable_grid_expansion_if_LV_limit_hit(n):
 
     n = pypsa.Network(snakemake.input.network)
 
+    adjust_renewable_profiles(n, snakemake.input, snakemake.params, year)
+
     add_build_year_to_new_assets(n, year)
 
     n_p = pypsa.Network(snakemake.input.network_p)

scripts/add_electricity.py

@@ -385,6 +385,10 @@ def attach_wind_and_solar(
             if ds.indexes["bus"].empty:
                 continue
 
+            # if-statement for compatibility with old profiles
+            if "year" in ds.indexes:
+                ds = ds.sel(year=ds.year.min(), drop=True)
+
             supcar = car.split("-", 2)[0]
             if supcar == "offwind":
                 underwater_fraction = ds["underwater_fraction"].to_pandas()

scripts/build_renewable_profiles.py

@@ -200,14 +200,21 @@
     if "snakemake" not in globals():
         from _helpers import mock_snakemake
 
-        snakemake = mock_snakemake("build_renewable_profiles", technology="solar")
+        snakemake = mock_snakemake("build_renewable_profiles", technology="offwind-dc")
     configure_logging(snakemake)
 
     nprocesses = int(snakemake.threads)
     noprogress = snakemake.config["run"].get("disable_progressbar", True)
     noprogress = noprogress or not snakemake.config["atlite"]["show_progress"]
     params = snakemake.params.renewable[snakemake.wildcards.technology]
     resource = params["resource"]  # pv panel params / wind turbine params
+
+    tech = next(t for t in ["panel", "turbine"] if t in resource)
+    models = resource[tech]
+    if not isinstance(models, dict):
+        models = {0: models}
+    resource[tech] = models[next(iter(models))]
+
     correction_factor = params.get("correction_factor", 1.0)
     capacity_per_sqkm = params["capacity_per_sqkm"]
     snapshots = snakemake.params.snapshots
@@ -323,22 +330,40 @@
     duration = time.time() - start
     logger.info(f"Completed average capacity factor calculation ({duration:2.2f}s)")
 
-    logger.info("Calculate weighted capacity factor time series...")
-    start = time.time()
+    profiles = []
+    capacities = []
+    for year, model in models.items():
 
-    profile, capacities = func(
-        matrix=availability.stack(spatial=["y", "x"]),
-        layout=layout,
-        index=buses,
-        per_unit=True,
-        return_capacity=True,
-        **resource,
-    )
+        logger.info(
+            f"Calculate weighted capacity factor time series for model {model}..."
+        )
+        start = time.time()
 
-    duration = time.time() - start
-    logger.info(
-        f"Completed weighted capacity factor time series calculation ({duration:2.2f}s)"
-    )
+        resource[tech] = model
+
+        profile, capacity = func(
+            matrix=availability.stack(spatial=["y", "x"]),
+            layout=layout,
+            index=buses,
+            per_unit=True,
+            return_capacity=True,
+            **resource,
+        )
+
+        dim = {"year": [year]}
+        profile = profile.expand_dims(dim)
+        capacity = capacity.expand_dims(dim)
+
+        profiles.append(profile.rename("profile"))
+        capacities.append(capacity.rename("weight"))
+
+        duration = time.time() - start
+        logger.info(
+            f"Completed weighted capacity factor time series calculation for model {model} ({duration:2.2f}s)"
+        )
+
+    profiles = xr.merge(profiles)
+    capacities = xr.merge(capacities)
 
     logger.info("Calculating maximal capacity per bus")
     p_nom_max = capacity_per_sqkm * availability @ area
@@ -365,8 +390,8 @@
 
     ds = xr.merge(
         [
-            (correction_factor * profile).rename("profile"),
-            capacities.rename("weight"),
+            correction_factor * profiles,
+            capacities,
             p_nom_max.rename("p_nom_max"),
             potential.rename("potential"),
             average_distance.rename("average_distance"),
@@ -386,9 +411,13 @@
         ds["underwater_fraction"] = xr.DataArray(underwater_fraction, [buses])
 
     # select only buses with some capacity and minimal capacity factor
+    mean_profile = ds["profile"].mean("time")
+    if "year" in ds.indexes:
+        mean_profile = mean_profile.max("year")
+
     ds = ds.sel(
         bus=(
-            (ds["profile"].mean("time") > params.get("min_p_max_pu", 0.0))
+            (mean_profile > params.get("min_p_max_pu", 0.0))
             & (ds["p_nom_max"] > params.get("min_p_nom_max", 0.0))
         )
     )

scripts/prepare_sector_network.py

@@ -421,6 +421,11 @@ def update_wind_solar_costs(n, costs):
         tech = "offwind-" + connection
         profile = snakemake.input["profile_offwind_" + connection]
         with xr.open_dataset(profile) as ds:
+
+            # if-statement for compatibility with old profiles
+            if "year" in ds.indexes:
+                ds = ds.sel(year=ds.year.min(), drop=True)
+
             underwater_fraction = ds["underwater_fraction"].to_pandas()
             connection_cost = (
                 snakemake.params.length_factor