bjoern/pypsa-eur
1
0
Fork 0
Code Issues Pull Requests Actions 1 Packages Projects Releases Wiki Activity

Fix grouping logic again

Browse Source
This commit is contained in:
Micha 2024-06-13 14:51:32 +02:00 committed by Michael Lindner
parent f2014c231a
commit 37bbbc6225
3 changed files with 20 additions and 13 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
config/config.default.yaml
View File

@ -390,8 +390,8 @@ solar_thermal:
# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#existing-capacities
existing_capacities:
grouping_years_power: [1895, 1920, 1950, 1955, 1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, 2025, 2030]
grouping_years_heat: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020] # 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]
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:

2
doc/release_notes.rst
View File

@ -19,6 +19,8 @@ Upcoming Release
<https://www.sciencedirect.com/science/article/pii/S0306261920312551>`__.
See configuration ``sector: enhanced_geothermal`` for details; by default switched off.
* Partially revert https://github.com/PyPSA/pypsa-eur/pull/967 to return to old grouping year logic (which was mostly correct)
PyPSA-Eur 0.11.0 (25th May 2024)
=====================================

27
scripts/add_existing_baseyear.py
View File

@ -201,19 +201,19 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
phased_out = df_agg[df_agg["DateOut"] < baseyear].index
df_agg.drop(phased_out, inplace=True)
older_assets = (df_agg.DateIn < min(grouping_years)).sum()
if older_assets:
newer_assets = (df_agg.DateIn > max(grouping_years)).sum()
if newer_assets:
logger.warning(
f"There are {older_assets} assets with build year "
f"before first power grouping year {min(grouping_years)}. "
f"There are {newer_assets} assets with build year "
f"after last power grouping year {max(grouping_years)}. "
"These assets are dropped and not considered."
"Consider to redefine the grouping years to keep them."
)
to_drop = df_agg[df_agg.DateIn < min(grouping_years)].index
to_drop = df_agg[df_agg.DateIn > max(grouping_years)].index
df_agg.drop(to_drop, inplace=True)
df_agg["grouping_year"] = np.take(
grouping_years[::-1], np.digitize(df_agg.DateIn, grouping_years[::-1])
grouping_years, np.digitize(df_agg.DateIn, grouping_years, right=True)
)
# calculate (adjusted) remaining lifetime before phase-out (+1 because assuming
@ -464,6 +464,11 @@ def add_heating_capacities_installed_before_baseyear(
else:
efficiency = costs.at[costs_name, "efficiency"]
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)
@ -473,12 +478,12 @@ def add_heating_capacities_installed_before_baseyear(
]
)
assert valid_grouping_years.is_monotonic_increasing
# get number of years of each interval
_years = (
valid_grouping_years.diff()
.shift(-1)
.fillna(baseyear - valid_grouping_years.iloc[-1])
)
_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()