electricity demand: remove powerstastics flag, merge sources in retrieve_electricity_demand
This commit is contained in:
Fabian
parent
672d7b9538
commit
9d4ce430cc
@ -1,5 +1,4 @@
|
||||
,Unit,Values,Description
|
||||
power_statistics,bool,"{true, false}",Whether to load the electricity consumption data of the ENTSOE power statistics (only for files from 2019 and before) or from the ENTSOE transparency data (only has load data from 2015 onwards).
|
||||
interpolate_limit,hours,integer,"Maximum gap size (consecutive nans) which interpolated linearly."
|
||||
time_shift_for_large_gaps,string,string,"Periods which are used for copying time-slices in order to fill large gaps of nans. Have to be valid ``pandas`` period strings."
|
||||
manual_adjustments,bool,"{true, false}","Whether to adjust the load data manually according to the function in :func:`manual_adjustment`."
|
||||
|
||||
|
@ -91,7 +91,7 @@ None.
|
||||
|
||||
**Outputs**
|
||||
|
||||
- ``data/load_raw.csv``
|
||||
- ``data/electricity_demand.csv``
|
||||
|
||||
|
||||
Rule ``retrieve_cost_data``
|
||||
|
||||
@ -24,7 +24,7 @@ rule build_electricity_demand:
|
||||
countries=config_provider("countries"),
|
||||
load=config_provider("load"),
|
||||
input:
|
||||
ancient("data/load_raw.csv"),
|
||||
ancient("data/electricity_demand.csv"),
|
||||
output:
|
||||
RESOURCES + "load.csv",
|
||||
log:
|
||||
|
||||
@ -159,7 +159,7 @@ if config["enable"]["retrieve"]:
|
||||
params:
|
||||
versions=["2019-06-05", "2020-10-06"],
|
||||
output:
|
||||
"data/load_raw.csv",
|
||||
"data/electricity_demand.csv",
|
||||
log:
|
||||
"logs/retrieve_electricity_demand.log",
|
||||
resources:
|
||||
|
||||
@ -31,7 +31,7 @@ Relevant Settings
|
||||
Inputs
|
||||
------
|
||||
|
||||
- ``data/load_raw.csv``:
|
||||
- ``data/electricity_demand.csv``:
|
||||
|
||||
Outputs
|
||||
-------
|
||||
@ -49,7 +49,7 @@ from _helpers import configure_logging, set_scenario_config
|
||||
from pandas import Timedelta as Delta
|
||||
|
||||
|
||||
def load_timeseries(fn, years, countries, powerstatistics=True):
|
||||
def load_timeseries(fn, years, countries):
|
||||
"""
|
||||
Read load data from OPSD time-series package version 2020-10-06.
|
||||
|
||||
@ -62,10 +62,6 @@ def load_timeseries(fn, years, countries, powerstatistics=True):
|
||||
File name or url location (file format .csv)
|
||||
countries : listlike
|
||||
Countries for which to read load data.
|
||||
powerstatistics: bool
|
||||
Whether the electricity consumption data of the ENTSOE power
|
||||
statistics (if true) or of the ENTSOE transparency map (if false)
|
||||
should be parsed.
|
||||
|
||||
Returns
|
||||
-------
|
||||
@ -74,17 +70,9 @@ def load_timeseries(fn, years, countries, powerstatistics=True):
|
||||
"""
|
||||
logger.info(f"Retrieving load data from '{fn}'.")
|
||||
|
||||
pattern = "power_statistics" if powerstatistics else "transparency"
|
||||
pattern = f"_load_actual_entsoe_{pattern}"
|
||||
|
||||
def rename(s):
|
||||
return s[: -len(pattern)]
|
||||
|
||||
return (
|
||||
pd.read_csv(fn, index_col=0, parse_dates=[0])
|
||||
.tz_localize(None)
|
||||
.filter(like=pattern)
|
||||
.rename(columns=rename)
|
||||
.dropna(how="all", axis=0)
|
||||
.rename(columns={"GB_UKM": "GB"})
|
||||
.filter(items=countries)
|
||||
@ -149,17 +137,18 @@ def copy_timeslice(load, cntry, start, stop, delta, fn_load=None):
|
||||
].values
|
||||
elif fn_load is not None:
|
||||
duration = pd.date_range(freq="h", start=start - delta, end=stop - delta)
|
||||
load_raw = load_timeseries(fn_load, duration, [cntry], powerstatistics)
|
||||
load_raw = load_timeseries(fn_load, duration, [cntry])
|
||||
load.loc[start:stop, cntry] = load_raw.loc[
|
||||
start - delta : stop - delta, cntry
|
||||
].values
|
||||
|
||||
|
||||
def manual_adjustment(load, fn_load, powerstatistics):
|
||||
def manual_adjustment(load, fn_load):
|
||||
"""
|
||||
Adjust gaps manual for load data from OPSD time-series package.
|
||||
|
||||
1. For the ENTSOE power statistics load data (if powerstatistics is True)
|
||||
1. For years later than 2015 for which the load data is mainly taken from the
|
||||
ENTSOE power statistics
|
||||
|
||||
Kosovo (KV) and Albania (AL) do not exist in the data set. Kosovo gets the
|
||||
same load curve as Serbia and Albania the same as Macdedonia, both scaled
|
||||
@ -167,7 +156,8 @@ def manual_adjustment(load, fn_load, powerstatistics):
|
||||
IEA Data browser [0] for the year 2013.
|
||||
|
||||
|
||||
2. For the ENTSOE transparency load data (if powerstatistics is False)
|
||||
2. For years earlier than 2015 for which the load data is mainly taken from the
|
||||
ENTSOE transparency platforms
|
||||
|
||||
Albania (AL) and Macedonia (MK) do not exist in the data set. Both get the
|
||||
same load curve as Montenegro, scaled by the corresponding ratio of total energy
|
||||
@ -183,9 +173,6 @@ def manual_adjustment(load, fn_load, powerstatistics):
|
||||
----------
|
||||
load : pd.DataFrame
|
||||
Load time-series with UTC timestamps x ISO-2 countries
|
||||
powerstatistics: bool
|
||||
Whether argument load comprises the electricity consumption data of
|
||||
the ENTSOE power statistics or of the ENTSOE transparency map
|
||||
load_fn: str
|
||||
File name or url location (file format .csv)
|
||||
|
||||
@ -195,88 +182,66 @@ def manual_adjustment(load, fn_load, powerstatistics):
|
||||
Manual adjusted and interpolated load time-series with UTC
|
||||
timestamps x ISO-2 countries
|
||||
"""
|
||||
if powerstatistics:
|
||||
if "MK" in load.columns:
|
||||
if "AL" not in load.columns or load.AL.isnull().values.all():
|
||||
load["AL"] = load["MK"] * (4.1 / 7.4)
|
||||
if "RS" in load.columns:
|
||||
if "KV" not in load.columns or load.KV.isnull().values.all():
|
||||
load["KV"] = load["RS"] * (4.8 / 27.0)
|
||||
if "MK" in load:
|
||||
if "AL" not in load or load.AL.isnull().values.all():
|
||||
load["AL"] = load["MK"] * (4.1 / 7.4)
|
||||
if "RS" in load:
|
||||
if "KV" not in load or load.KV.isnull().values.all():
|
||||
load["KV"] = load["RS"] * (4.8 / 27.0)
|
||||
if "ME" in load:
|
||||
if "AL" not in load and "AL" in countries:
|
||||
load["AL"] = load.ME * (5.7 / 2.9)
|
||||
if "MK" not in load and "MK" in countries:
|
||||
load["MK"] = load.ME * (6.7 / 2.9)
|
||||
if "BA" not in load and "BA" in countries:
|
||||
load["BA"] = load.HR * (11.0 / 16.2)
|
||||
|
||||
copy_timeslice(
|
||||
load, "GR", "2015-08-11 21:00", "2015-08-15 20:00", Delta(weeks=1)
|
||||
)
|
||||
copy_timeslice(
|
||||
load, "AT", "2018-12-31 22:00", "2019-01-01 22:00", Delta(days=2)
|
||||
)
|
||||
copy_timeslice(
|
||||
load, "CH", "2010-01-19 07:00", "2010-01-19 22:00", Delta(days=1)
|
||||
)
|
||||
copy_timeslice(
|
||||
load, "CH", "2010-03-28 00:00", "2010-03-28 21:00", Delta(days=1)
|
||||
)
|
||||
# is a WE, so take WE before
|
||||
copy_timeslice(
|
||||
load, "CH", "2010-10-08 13:00", "2010-10-10 21:00", Delta(weeks=1)
|
||||
)
|
||||
copy_timeslice(
|
||||
load, "CH", "2010-11-04 04:00", "2010-11-04 22:00", Delta(days=1)
|
||||
)
|
||||
copy_timeslice(
|
||||
load, "NO", "2010-12-09 11:00", "2010-12-09 18:00", Delta(days=1)
|
||||
)
|
||||
# whole january missing
|
||||
copy_timeslice(
|
||||
load,
|
||||
"GB",
|
||||
"2010-01-01 00:00",
|
||||
"2010-01-31 23:00",
|
||||
Delta(days=-365),
|
||||
fn_load,
|
||||
)
|
||||
# 1.1. at midnight gets special treatment
|
||||
copy_timeslice(
|
||||
load,
|
||||
"IE",
|
||||
"2016-01-01 00:00",
|
||||
"2016-01-01 01:00",
|
||||
Delta(days=-366),
|
||||
fn_load,
|
||||
)
|
||||
copy_timeslice(
|
||||
load,
|
||||
"PT",
|
||||
"2016-01-01 00:00",
|
||||
"2016-01-01 01:00",
|
||||
Delta(days=-366),
|
||||
fn_load,
|
||||
)
|
||||
copy_timeslice(
|
||||
load,
|
||||
"GB",
|
||||
"2016-01-01 00:00",
|
||||
"2016-01-01 01:00",
|
||||
Delta(days=-366),
|
||||
fn_load,
|
||||
)
|
||||
copy_timeslice(load, "GR", "2015-08-11 21:00", "2015-08-15 20:00", Delta(weeks=1))
|
||||
copy_timeslice(load, "AT", "2018-12-31 22:00", "2019-01-01 22:00", Delta(days=2))
|
||||
copy_timeslice(load, "CH", "2010-01-19 07:00", "2010-01-19 22:00", Delta(days=1))
|
||||
copy_timeslice(load, "CH", "2010-03-28 00:00", "2010-03-28 21:00", Delta(days=1))
|
||||
# is a WE, so take WE before
|
||||
copy_timeslice(load, "CH", "2010-10-08 13:00", "2010-10-10 21:00", Delta(weeks=1))
|
||||
copy_timeslice(load, "CH", "2010-11-04 04:00", "2010-11-04 22:00", Delta(days=1))
|
||||
copy_timeslice(load, "NO", "2010-12-09 11:00", "2010-12-09 18:00", Delta(days=1))
|
||||
# whole january missing
|
||||
copy_timeslice(
|
||||
load,
|
||||
"GB",
|
||||
"2010-01-01 00:00",
|
||||
"2010-01-31 23:00",
|
||||
Delta(days=-365),
|
||||
fn_load,
|
||||
)
|
||||
# 1.1. at midnight gets special treatment
|
||||
copy_timeslice(
|
||||
load,
|
||||
"IE",
|
||||
"2016-01-01 00:00",
|
||||
"2016-01-01 01:00",
|
||||
Delta(days=-366),
|
||||
fn_load,
|
||||
)
|
||||
copy_timeslice(
|
||||
load,
|
||||
"PT",
|
||||
"2016-01-01 00:00",
|
||||
"2016-01-01 01:00",
|
||||
Delta(days=-366),
|
||||
fn_load,
|
||||
)
|
||||
copy_timeslice(
|
||||
load,
|
||||
"GB",
|
||||
"2016-01-01 00:00",
|
||||
"2016-01-01 01:00",
|
||||
Delta(days=-366),
|
||||
fn_load,
|
||||
)
|
||||
|
||||
else:
|
||||
if "ME" in load:
|
||||
if "AL" not in load and "AL" in countries:
|
||||
load["AL"] = load.ME * (5.7 / 2.9)
|
||||
if "MK" not in load and "MK" in countries:
|
||||
load["MK"] = load.ME * (6.7 / 2.9)
|
||||
if "BA" not in load and "BA" in countries:
|
||||
load["BA"] = load.HR * (11.0 / 16.2)
|
||||
copy_timeslice(
|
||||
load, "BG", "2018-10-27 21:00", "2018-10-28 22:00", Delta(weeks=1)
|
||||
)
|
||||
copy_timeslice(
|
||||
load, "LU", "2019-01-02 11:00", "2019-01-05 05:00", Delta(weeks=-1)
|
||||
)
|
||||
copy_timeslice(
|
||||
load, "LU", "2019-02-05 20:00", "2019-02-06 19:00", Delta(weeks=-1)
|
||||
)
|
||||
copy_timeslice(load, "BG", "2018-10-27 21:00", "2018-10-28 22:00", Delta(weeks=1))
|
||||
copy_timeslice(load, "LU", "2019-01-02 11:00", "2019-01-05 05:00", Delta(weeks=-1))
|
||||
copy_timeslice(load, "LU", "2019-02-05 20:00", "2019-02-06 19:00", Delta(weeks=-1))
|
||||
|
||||
return load
|
||||
|
||||
@ -290,17 +255,16 @@ if __name__ == "__main__":
|
||||
configure_logging(snakemake)
|
||||
set_scenario_config(snakemake)
|
||||
|
||||
powerstatistics = snakemake.params.load["power_statistics"]
|
||||
interpolate_limit = snakemake.params.load["interpolate_limit"]
|
||||
countries = snakemake.params.countries
|
||||
snapshots = pd.date_range(freq="h", **snakemake.params.snapshots)
|
||||
years = slice(snapshots[0], snapshots[-1])
|
||||
time_shift = snakemake.params.load["time_shift_for_large_gaps"]
|
||||
|
||||
load = load_timeseries(snakemake.input[0], years, countries, powerstatistics)
|
||||
load = load_timeseries(snakemake.input[0], years, countries)
|
||||
|
||||
if snakemake.params.load["manual_adjustments"]:
|
||||
load = manual_adjustment(load, snakemake.input[0], powerstatistics)
|
||||
load = manual_adjustment(load, snakemake.input[0])
|
||||
|
||||
if load.empty:
|
||||
logger.warning("Build electricity demand time series is empty.")
|
||||
|
||||
@ -20,7 +20,7 @@ if __name__ == "__main__":
|
||||
if "snakemake" not in globals():
|
||||
from _helpers import mock_snakemake
|
||||
|
||||
snakemake = mock_snakemake("retrieve_eletricity_demand")
|
||||
snakemake = mock_snakemake("retrieve_electricity_demand")
|
||||
rootpath = ".."
|
||||
else:
|
||||
rootpath = "."
|
||||
@ -33,5 +33,17 @@ if __name__ == "__main__":
|
||||
pd.read_csv(url.format(version=version), index_col=0)
|
||||
for version in snakemake.params.versions
|
||||
]
|
||||
res = pd.concat([df1, df2[df2.index > df1.index[-1]]], join="inner")
|
||||
combined = pd.concat([df1, df2[df2.index > df1.index[-1]]])
|
||||
|
||||
pattern = "_load_actual_entsoe_transparency"
|
||||
transparency = combined.filter(like=pattern).rename(
|
||||
columns=lambda x: x.replace(pattern, "")
|
||||
)
|
||||
pattern = "_load_actual_entsoe_power_statistics"
|
||||
powerstatistics = combined.filter(like=pattern).rename(
|
||||
columns=lambda x: x.replace(pattern, "")
|
||||
)
|
||||
|
||||
res = transparency.fillna(powerstatistics)
|
||||
|
||||
res.to_csv(snakemake.output[0])
|
||||
|
||||
Loading…
Reference in New Issue
Block a user