add option to vary parameter (#1244)

* add option to vary parameter

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* remove logger.info

* adjust maybe_adjust_costs_and_potentials

* update configtables

* revert removed cost_factor

* reset build_energy_totals to master

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* add release notes

* Revert "revert removed cost_factor"

This reverts commit b7154f046954bd6de34c2910f3f9f52b44d5f233.

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Fabian Neumann <fabian.neumann@outlook.de>

config/config.default.yaml

@@ -662,7 +662,6 @@ sector:
   use_electrolysis_waste_heat: 0.25
   electricity_transmission_grid: true
   electricity_distribution_grid: true
-  electricity_distribution_grid_cost_factor: 1.0
   electricity_grid_connection: true
   transmission_efficiency:
     DC:
@@ -871,7 +870,12 @@ clustering:
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#adjustments
 adjustments:
   electricity: false
-  sector: false
+  sector:
+    factor:
+      Link:
+        electricity distribution grid:
+          capital_cost: 1.0
+    absolute: false
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#solving
 solving:

doc/configtables/adjustments.csv

@@ -1,8 +1,14 @@
-,Unit,Values,Description
-adjustments,,,
--- electricity,bool or dict,,"Parameter adjustments for capital cost, marginal cost, and maximum capacities of carriers. Applied in :mod:`prepare_network.`"
--- -- {attr},,,"Attribute can be ``e_nom_opt``, ``p_nom_opt``, ``marginal_cost`` or ``capital_cost``"
--- -- -- {carrier},float,per-unit,"Any carrier of the network to which parameter adjustment factor should be applied."
--- sector,bool or dict,,"Parameter adjustments for capital cost, marginal cost, and maximum capacities of carriers. Applied in :mod:`prepare_sector_network.`"
--- -- {attr},,,"Attribute can be ``e_nom_opt``, ``p_nom_opt``, ``marginal_cost`` or ``capital_cost``"
--- -- -- {carrier},float,per-unit,"Any carrier of the network to which parameter adjustment factor should be applied."
+,Unit,Values,Description
+adjustments,,,
+-- electricity,bool or dict,,Parameter adjustments applied in :mod:`prepare_network.`
+-- -- factor,,,Multiply original value with given factor
+-- -- absolute,,,Set attribute to absolute value
+-- -- -- {component},,,PyPSA component in :mod:`prepare_network.`
+-- -- -- -- {carrier},,,Any carrier of the network to which parameter adjustment factor should be applied.
+-- -- -- --  -- {attr},float,per-unit,Attribute to which parameter adjustment factor should be applied.
+-- sector,bool or dict,,Parameter adjustments applied in :mod:`prepare_sector_network.`
+-- -- factor,,,Multiply original value with given factor
+-- -- absolute,,,Set attribute to absolute value
+-- -- -- {component},,,PyPSA component in :mod:`prepare_network.`
+-- -- -- -- {carrier},,,Any carrier of the network to which parameter adjustment factor should be applied.
+-- -- -- --  -- {attr},Float or dict,per-unit,Attribute to which parameter adjustment factor should be applied. Can be also a dictionary with planning horizons as keys.

doc/release_notes.rst

@@ -10,6 +10,7 @@ Release Notes
 
 .. Upcoming Release
 
+* Add function ``modify_attribute`` which allows to adjust every attribute of every PyPSA component either by a multiplication with a factor or setting an absolute value. These adjustments can also depend on the planning horizons and are set in the config under ``adjustments``. The function ``maybe_adjust_costs_and_potentials`` is removed.
 
 * Add technology options for methanol, like electricity production from methanol, biomass to methanol, methanol to kerosene, ...
 

scripts/_helpers.py

@@ -282,6 +282,38 @@ def aggregate_p(n):
     )
 
 
+def get(item, investment_year=None):
+    """
+    Check whether item depends on investment year.
+    """
+    if not isinstance(item, dict):
+        return item
+    elif investment_year in item.keys():
+        return item[investment_year]
+    else:
+        logger.warning(
+            f"Investment key {investment_year} not found in dictionary {item}."
+        )
+        keys = sorted(item.keys())
+        if investment_year < keys[0]:
+            logger.warning(f"Lower than minimum key. Taking minimum key {keys[0]}")
+            return item[keys[0]]
+        elif investment_year > keys[-1]:
+            logger.warning(f"Higher than maximum key. Taking maximum key {keys[0]}")
+            return item[keys[-1]]
+        else:
+            logger.warning(
+                "Interpolate linearly between the next lower and next higher year."
+            )
+            lower_key = max(k for k in keys if k < investment_year)
+            higher_key = min(k for k in keys if k > investment_year)
+            lower = item[lower_key]
+            higher = item[higher_key]
+            return lower + (higher - lower) * (investment_year - lower_key) / (
+                higher_key - lower_key
+            )
+
+
 def aggregate_e_nom(n):
     return pd.concat(
         [

scripts/prepare_network.py

@@ -64,6 +64,7 @@ import pandas as pd
 import pypsa
 from _helpers import (
     configure_logging,
+    get,
     set_scenario_config,
     update_config_from_wildcards,
 )
@@ -75,26 +76,43 @@ idx = pd.IndexSlice
 logger = logging.getLogger(__name__)
 
 
-def maybe_adjust_costs_and_potentials(n, adjustments):
+def modify_attribute(n, adjustments, investment_year, modification="factor"):
+    if not adjustments[modification]:
+        return
+    change_dict = adjustments[modification]
+    for c in change_dict.keys():
+        if c not in n.components.keys():
+            logger.warning(f"{c} needs to be a PyPSA Component")
+            continue
+        for carrier in change_dict[c].keys():
+            ind_i = n.df(c)[n.df(c).carrier == carrier].index
+            if ind_i.empty:
+                continue
+            for parameter in change_dict[c][carrier].keys():
+                if parameter not in n.df(c).columns:
+                    logger.warning(f"Attribute {parameter} needs to be in {c} columns.")
+                    continue
+                if investment_year:
+                    factor = get(change_dict[c][carrier][parameter], investment_year)
+                else:
+                    factor = change_dict[c][carrier][parameter]
+                if modification == "factor":
+                    logger.info(f"Modify {parameter} of {carrier} by factor {factor} ")
+                    n.df(c).loc[ind_i, parameter] *= factor
+                elif modification == "absolute":
+                    logger.info(f"Set {parameter} of {carrier} to {factor} ")
+                    n.df(c).loc[ind_i, parameter] = factor
+                else:
+                    logger.warning(
+                        f"{modification} needs to be either 'absolute' or 'factor'."
+                    )
+
+
+def maybe_adjust_costs_and_potentials(n, adjustments, investment_year=None):
     if not adjustments:
         return
-
-    for attr, carrier_factor in adjustments.items():
-        for carrier, factor in carrier_factor.items():
-            # beware if factor is 0 and p_nom_max is np.inf, 0*np.inf is nan
-            if carrier == "AC":  # lines do not have carrier
-                n.lines[attr] *= factor
-                continue
-            comps = {
-                "p_nom_max": {"Generator", "Link", "StorageUnit"},
-                "e_nom_max": {"Store"},
-                "capital_cost": {"Generator", "Link", "StorageUnit", "Store"},
-                "marginal_cost": {"Generator", "Link", "StorageUnit", "Store"},
-            }
-            for c in n.iterate_components(comps[attr]):
-                sel = c.df.index[c.df.carrier == carrier]
-                c.df.loc[sel, attr] *= factor
-        logger.info(f"changing {attr} for {carrier} by factor {factor}")
+    for modification in adjustments.keys():
+        modify_attribute(n, adjustments, investment_year, modification)
 
 
 def add_co2limit(n, co2limit, Nyears=1.0):
@@ -300,6 +318,7 @@ def set_line_nom_max(
     n.links["p_nom_max"] = n.links.p_nom_max.clip(upper=p_nom_max_set)
 
 
+# %%
 if __name__ == "__main__":
     if "snakemake" not in globals():
         from _helpers import mock_snakemake

scripts/prepare_sector_network.py

@@ -19,6 +19,7 @@ import pypsa
 import xarray as xr
 from _helpers import (
     configure_logging,
+    get,
     set_scenario_config,
     update_config_from_wildcards,
 )
@@ -241,38 +242,6 @@ def determine_emission_sectors(options):
     return sectors
 
 
-def get(item, investment_year=None):
-    """
-    Check whether item depends on investment year.
-    """
-    if not isinstance(item, dict):
-        return item
-    elif investment_year in item.keys():
-        return item[investment_year]
-    else:
-        logger.warning(
-            f"Investment key {investment_year} not found in dictionary {item}."
-        )
-        keys = sorted(item.keys())
-        if investment_year < keys[0]:
-            logger.warning(f"Lower than minimum key. Taking minimum key {keys[0]}")
-            return item[keys[0]]
-        elif investment_year > keys[-1]:
-            logger.warning(f"Higher than maximum key. Taking maximum key {keys[0]}")
-            return item[keys[-1]]
-        else:
-            logger.warning(
-                "Interpolate linearly between the next lower and next higher year."
-            )
-            lower_key = max(k for k in keys if k < investment_year)
-            higher_key = min(k for k in keys if k > investment_year)
-            lower = item[lower_key]
-            higher = item[higher_key]
-            return lower + (higher - lower) * (investment_year - lower_key) / (
-                higher_key - lower_key
-            )
-
-
 def co2_emissions_year(
     countries, input_eurostat, options, emissions_scope, input_co2, year
 ):
@@ -1313,12 +1282,6 @@ def insert_electricity_distribution_grid(n, costs):
     # TODO pop_layout?
     # TODO options?
 
-    cost_factor = options["electricity_distribution_grid_cost_factor"]
-
-    logger.info(
-        f"Inserting electricity distribution grid with investment cost factor of {cost_factor:.2f}"
-    )
-
     nodes = pop_layout.index
 
     n.madd(
@@ -1339,7 +1302,7 @@ def insert_electricity_distribution_grid(n, costs):
         carrier="electricity distribution grid",
         efficiency=1,
         lifetime=costs.at["electricity distribution grid", "lifetime"],
-        capital_cost=costs.at["electricity distribution grid", "fixed"] * cost_factor,
+        capital_cost=costs.at["electricity distribution grid", "fixed"],
     )
 
     # deduct distribution losses from electricity demand as these are included in total load
@@ -4794,8 +4757,6 @@ if __name__ == "__main__":
             n, snakemake.input["egs_potentials"], snakemake.input["egs_overlap"], costs
         )
 
-    maybe_adjust_costs_and_potentials(n, snakemake.params["adjustments"])
-
     if options["gas_distribution_grid"]:
         insert_gas_distribution_costs(n, costs)
 
@@ -4821,6 +4782,10 @@ if __name__ == "__main__":
     if options.get("cluster_heat_buses", False) and not first_year_myopic:
         cluster_heat_buses(n)
 
+    maybe_adjust_costs_and_potentials(
+        n, snakemake.params["adjustments"], investment_year
+    )
+
     n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
 
     sanitize_carriers(n, snakemake.config)