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

build_heat_totals: use more years for regression

Browse Source
This commit is contained in:
Fabian Neumann 2024-03-14 14:09:39 +01:00
parent cbeb9834ac
commit 8aa4b5b558
1 changed files with 12 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
scripts/build_heat_totals.py
View File

@ -15,17 +15,22 @@ idx = pd.IndexSlice
def approximate_heat_demand(energy_totals, hdd): def approximate_heat_demand(energy_totals, hdd):
if isinstance(hdd, str):
hdd = pd.read_csv(hdd, index_col=0).T countries = hdd.columns
hdd.index = hdd.index.astype(int)
demands = {} demands = {}
for kind, sector in product(["total", "electricity"], ["services", "residential"]): for kind, sector in product(["total", "electricity"], ["services", "residential"]):
row = idx[:, 2007:2015] # reduced number years (2007-2021) for regression because it implicitly
# assumes a constant building stock
row = idx[:, 2007:2021]
col = f"{kind} {sector} space" col = f"{kind} {sector} space"
demand = energy_totals.loc[row, col].unstack(0) demand = energy_totals.loc[row, col].unstack(0)
# ffill for GB in 2020- and bfill for CH 2007-2009
# compromise to have more years available for the fit
demand = demand.ffill(axis=0).bfill(axis=0)
demand_approx = {} demand_approx = {}
for c in countries: for c in countries:
@ -62,16 +67,15 @@ def approximate_heat_demand(energy_totals, hdd):
if __name__ == "__main__": if __name__ == "__main__":
if "snakemake" not in globals(): if "snakemake" not in globals():
from helper import mock_snakemake from _helpers import mock_snakemake
snakemake = mock_snakemake("build_energy_totals") snakemake = mock_snakemake("build_heat_totals")
hdd = pd.read_csv(snakemake.input.hdd, index_col=0).T hdd = pd.read_csv(snakemake.input.hdd, index_col=0).T
hdd.index = hdd.index.astype(int)
energy_totals = pd.read_csv(snakemake.input.energy_totals, index_col=[0, 1]) energy_totals = pd.read_csv(snakemake.input.energy_totals, index_col=[0, 1])
countries = hdd.columns
heat_demand = approximate_heat_demand(energy_totals, hdd) heat_demand = approximate_heat_demand(energy_totals, hdd)
heat_demand.to_csv(snakemake.output.heat_totals) heat_demand.to_csv(snakemake.output.heat_totals)