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bugfixes for manual load adjustments

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This commit is contained in:
martacki 2022-04-29 15:09:10 +02:00
parent 49f1c0f629
commit 8a49697a51
3 changed files with 20 additions and 8 deletions
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2
config.default.yaml
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@ -26,7 +26,7 @@ clustering:
snapshots: snapshots:
start: "2013-01-01" start: "2013-01-01"
end: "2014-01-01" end: "2014-01-01"
closed: 'left' # end is not inclusive inclusive: 'left' # end is not inclusive
enable: enable:
prepare_links_p_nom: false prepare_links_p_nom: false

2
config.tutorial.yaml
View File

@ -26,7 +26,7 @@ clustering:
snapshots: snapshots:
start: "2013-03-01" start: "2013-03-01"
end: "2013-04-01" end: "2013-04-01"
closed: 'left' # end is not inclusive inclusive: 'left' # end is not inclusive
enable: enable:
prepare_links_p_nom: false prepare_links_p_nom: false

24
scripts/build_load_data.py
View File

@ -116,14 +116,20 @@ def nan_statistics(df):
keys=['total', 'consecutive', 'max_total_per_month'], axis=1) keys=['total', 'consecutive', 'max_total_per_month'], axis=1)
def copy_timeslice(load, cntry, start, stop, delta): def copy_timeslice(load, cntry, start, stop, delta, fn_load=None):
start = pd.Timestamp(start) start = pd.Timestamp(start)
stop = pd.Timestamp(stop) stop = pd.Timestamp(stop)
if start-delta in load.index and stop in load.index and cntry in load: if (start in load.index and stop in load.index):
load.loc[start:stop, cntry] = load.loc[start-delta:stop-delta, cntry].values if start-delta in load.index and stop-delta in load.index and cntry in load:
load.loc[start:stop, cntry] = load.loc[start-delta:stop-delta, cntry].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)
if start-delta in load_raw.index and stop-delta in load_raw.index and cntry in load_raw:
load.loc[start:stop, cntry] = load_raw.loc[start-delta:stop-delta, cntry].values
def manual_adjustment(load, powerstatistics): def manual_adjustment(load, fn_load, powerstatistics):
""" """
Adjust gaps manual for load data from OPSD time-series package. Adjust gaps manual for load data from OPSD time-series package.
@ -150,6 +156,8 @@ def manual_adjustment(load, powerstatistics):
powerstatistics: bool powerstatistics: bool
Whether argument load comprises the electricity consumption data of Whether argument load comprises the electricity consumption data of
the ENTSOE power statistics or of the ENTSOE transparency map the ENTSOE power statistics or of the ENTSOE transparency map
load_fn: str
File name or url location (file format .csv)
Returns Returns
------- -------
@ -175,7 +183,11 @@ def manual_adjustment(load, powerstatistics):
copy_timeslice(load, 'CH', '2010-11-04 04:00', '2010-11-04 22:00', Delta(days=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)) copy_timeslice(load, 'NO', '2010-12-09 11:00', '2010-12-09 18:00', Delta(days=1))
# whole january missing # whole january missing
copy_timeslice(load, 'GB', '2009-12-31 23:00', '2010-01-31 23:00', Delta(days=-364)) 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: else:
if 'ME' in load: if 'ME' in load:
@ -206,7 +218,7 @@ if __name__ == "__main__":
load = load_timeseries(snakemake.input[0], years, countries, powerstatistics) load = load_timeseries(snakemake.input[0], years, countries, powerstatistics)
if snakemake.config['load']['manual_adjustments']: if snakemake.config['load']['manual_adjustments']:
load = manual_adjustment(load, powerstatistics) load = manual_adjustment(load, snakemake.input[0], powerstatistics)
logger.info(f"Linearly interpolate gaps of size {interpolate_limit} and less.") logger.info(f"Linearly interpolate gaps of size {interpolate_limit} and less.")
load = load.interpolate(method='linear', limit=interpolate_limit) load = load.interpolate(method='linear', limit=interpolate_limit)