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enh(add_existing_baseyear): Pull out valid_grouping_years algorithm from heat #1570

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enh(add_existing_baseyear): Pull out valid_grouping_years algorithm from heat #1570

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4 changes: 2 additions & 2 deletions config/config.default.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -429,8 +429,8 @@ solar_thermal:

# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#existing-capacities
existing_capacities:
grouping_years_power: [1920, 1950, 1955, 1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, 2025]
grouping_years_heat: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019] # heat grouping years >= baseyear will be ignored
grouping_years_power: [1920, 1950, 1955, 1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, 2025] # power grouping years > baseyear will be ignored
grouping_years_heat: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019] # heat grouping years > baseyear will be ignored
threshold_capacity: 10
default_heating_lifetime: 20
conventional_carriers:
Expand Down
65 changes: 37 additions & 28 deletions scripts/add_existing_baseyear.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
"""

import logging
from collections.abc import Sequence
from types import SimpleNamespace

import country_converter as coco
Expand Down Expand Up @@ -464,6 +465,25 @@ def get_efficiency(
return efficiency


def valid_grouping_years(
grouping_years: Sequence[int] | pd.Index,
baseyear: int,
max_lifetime: float | None = None,
) -> pd.Index:
grouping_years = pd.Index(sorted(grouping_years)).astype(int)

valid = grouping_years <= baseyear
if max_lifetime is not None:
valid &= grouping_years + max_lifetime >= baseyear
if not valid.all():
logger.warning(
"Only grouping years between [baseyear - max. lifetime, baseyear] are used."
f"Dropping {grouping_years[~valid]}."
)

return grouping_years[valid]


def add_heating_capacities_installed_before_baseyear(
n: pypsa.Network,
costs: pd.DataFrame,
Expand All @@ -490,7 +510,7 @@ def add_heating_capacities_installed_before_baseyear(
Technology costs
baseyear : int
Base year for analysis
grouping_years : list
grouping_years : pd.Index
Intervals to group capacities
heat_pump_cop : xr.DataArray
Heat pump coefficients of performance
Expand Down Expand Up @@ -532,32 +552,14 @@ def add_heating_capacities_installed_before_baseyear(
else:
nodes_elec = nodes

too_large_grouping_years = [
gy for gy in grouping_years if gy >= int(baseyear)
]
if too_large_grouping_years:
logger.warning(
f"Grouping years >= baseyear are ignored. Dropping {too_large_grouping_years}."
)
valid_grouping_years = pd.Series(
[
int(grouping_year)
for grouping_year in grouping_years
if int(grouping_year) + default_lifetime > int(baseyear)
and int(grouping_year) < int(baseyear)
]
)

assert valid_grouping_years.is_monotonic_increasing

# get number of years of each interval
_years = valid_grouping_years.diff()
# Fill NA from .diff() with value for the first interval
_years[0] = valid_grouping_years[0] - baseyear + default_lifetime
# Installation is assumed to be linear for the past
ratios = _years / _years.sum()
# get number of years of each interval
_years = pd.Index([grouping_years[0] - baseyear + default_lifetime]).append(
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I am a bit confused about this expression here, this can be a negative number or? If grouping_year[0] == 1990 and baseyear == 2020 and lifetime == 20 for example.

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I must admit, i did not think about this. It is a literal port of Amos':

# Fill NA from .diff() with value for the first interval
_years[0] = valid_grouping_years[0] - baseyear + default_lifetime

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@coroa coroa Mar 11, 2025 •
edited
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Ok, sorry, Amos, i was wrongly blaming you. The origin story of that expression is complicated.

@lisazeyen came up with:
https://github.com/PyPSA/pypsa-eur/blame/a72388b989d1d667ec7e44d66f6c3b494b46d000/scripts/add_existing_baseyear.py#L466-L467

         _years = (valid_grouping_years.diff().shift(-1)
                  .fillna(baseyear-valid_grouping_years.iloc[-1]))

ie. (baseyear - last of grouping_years) which sounds quite sensible (for an interval, unless the last grouping year is the same as the baseyear).

and then @lindnemi changed it to:

# Fill NA from .diff() with value for the first interval
_years[0] = valid_grouping_years[0] - baseyear + default_lifetime

in #1102 with associated discussion in #1091 .

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It sounds like there was some back and forth, i'll not try to understand this fully now, maybe its best to have a short discussion.

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Sorry for the late reply @coroa! I think I only made some small refactoring changes here. I'll be OOO for a week but happy to discuss this further then, if helpful.

grouping_years.diff()
)
# Installation is assumed to be linear for the past
ratios = _years / np.sum(_years)

for ratio, grouping_year in zip(ratios, valid_grouping_years):
for ratio, grouping_year in zip(ratios, grouping_years):
# Add heat pumps
for heat_source in heat_pump_source_types[heat_system.system_type.value]:
costs_name = heat_system.heat_pump_costs_name(heat_source)
Expand Down Expand Up @@ -732,8 +734,10 @@ def add_heating_capacities_installed_before_baseyear(
Nyears,
)

grouping_years_power = snakemake.params.existing_capacities["grouping_years_power"]
grouping_years_heat = snakemake.params.existing_capacities["grouping_years_heat"]
grouping_years_power = valid_grouping_years(
snakemake.params.existing_capacities["grouping_years_power"],
baseyear,
)
add_power_capacities_installed_before_baseyear(
n=n,
costs=costs,
Expand All @@ -751,6 +755,11 @@ def add_heating_capacities_installed_before_baseyear(
year = int(snakemake.params["energy_totals_year"])
heating_efficiencies = pd.read_csv(fn, index_col=[1, 0]).loc[year]

grouping_years_heat = valid_grouping_years(
snakemake.params.existing_capacities["grouping_years_heat"],
baseyear,
snakemake.params.existing_capacities["default_heating_lifetime"],
)
add_heating_capacities_installed_before_baseyear(
n=n,
costs=costs,
Expand Down
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