* ammonia_production: minor cleaning and move into __main__ (#106) * biomass_potentials: code cleaning and automatic country index inferral (#107) * Revision: build energy totals (#111) * blacken * energy_totals: preliminaries * energy_totals: update build_swiss * energy_totals: update build_eurostat * energy_totals: update build_idees * energy_totals: update build_energy_totals * energy_totals: update build_eea_co2 * energy_totals: update build_eurostat_co2 * energy_totals: update build_co2_totals * energy_totals: update build_transport_data * energy_totals: add tqdm progressbar to idees * energy_totals: adjust __main__ section * energy_totals: handle inputs via Snakefile and config * energy_totals: handle data and emissions year via config * energy_totals: fix reading in eurostat for different years * energy_totals: fix erroneous drop duplicates This caused problems for waste management in HU and SI * energy_totals: make scope selection of CO2 or GHG a config option * Revision: build industrial production per country (#114) * industry-ppc: format * industry-ppc: rewrite for performance * industry-ppc: move reference year to config * industry-ppct: tidy up and format (#115) * remove stale industry demand rules (#116) * industry-epc: rewrite for performance (#117) * Revision: industrial distribution key (#118) * industry-distribution: first tidying * industry-distribution: first tidying * industry-distribution: fix syntax * Revision: industrial energy demand per node today (#119) * industry-epn: minor code cleaning * industry-epn: remove accidental artifact * industry-epn: remove accidental artifact II * industry-ppn: code cleaning (#120) * minor code cleaning (#121) * Revision: industry sector ratios (#122) * sector-ratios: basic reformatting * sector-ratios: add new read_excel function that filters year already * sector-ratios: rename jrc to idees * sector-ratios: rename conv_factor to toe_to_MWh * sector-ratios: modularise into functions * Move overriding of component attributes to function and into data (#123) * move overriding of component attributes to central function and store in separate folder * fix return of helper.override_component_attrs * prepare: fix accidental syntax error * override_component_attrs: bugfix that aligns with pypsa components * Revision: build population layout (#108) * population_layouts: move inside __main__ and blacken * population_layouts: misc code cleaning and multiprocessing * population_layouts: fix fill_values assignment of urban fractions * population_layouts: bugfig for UK-GB naming ambiguity * population_layouts: sort countries alphabetically for better overview * config: change path to atlite cutout * Revision: build clustered population layouts (#112) * population_layouts: move inside __main__ and blacken * population_layouts: misc code cleaning and multiprocessing * population_layouts: fix fill_values assignment of urban fractions * population_layouts: bugfig for UK-GB naming ambiguity * population_layouts: sort countries alphabetically for better overview * cl_pop_layout: blacken * cl_pop_layout: turn GeoDataFrame into GeoSeries + code cleaning * cl_pop_layout: add fraction column which is repeatedly calculated downstream * Revision: build various heating-related time series (#113) * population_layouts: move inside __main__ and blacken * population_layouts: misc code cleaning and multiprocessing * population_layouts: fix fill_values assignment of urban fractions * population_layouts: bugfig for UK-GB naming ambiguity * population_layouts: sort countries alphabetically for better overview * cl_pop_layout: blacken * cl_pop_layout: turn GeoDataFrame into GeoSeries + code cleaning * gitignore: add .vscode * heating_profiles: update to new atlite and move into __main__ * heating_profiles: remove extra cutout * heating_profiles: load regions with .buffer(0) and remove clean_invalid_geometries * heating_profiles: load regions with .buffer(0) before squeeze() * heating_profiles: account for transpose of dataarray * heating_profiles: account for transpose of dataarray in add_exiting_baseyear * Reduce verbosity of Snakefile (2) (#128) * tidy Snakefile light * Snakefile: fix indents * Snakefile: add missing RDIR * tidy config by removing quotes and expanding lists (#109) * bugfix: reorder squeeze() and buffer() * plot/summary: cosmetic changes including: (#131) - matplotlibrc for default style and backend - remove unused config options - option to configure geomap colors - option to configure geomap bounds * solve: align with pypsa-eur using ilopf (#129) * tidy myopic code scripts (#132) * use mock_snakemake from pypsa-eur (#133) * Snakefile: add benchmark files to each rule * Snakefile: only run build_retro_cost if endogenously optimised * Snakefile: remove old {network} wildcard constraints * WIP: Revision: prepare_sector_network (#124) * population_layouts: move inside __main__ and blacken * population_layouts: misc code cleaning and multiprocessing * population_layouts: fix fill_values assignment of urban fractions * population_layouts: bugfig for UK-GB naming ambiguity * population_layouts: sort countries alphabetically for better overview * cl_pop_layout: blacken * cl_pop_layout: turn GeoDataFrame into GeoSeries + code cleaning * move overriding of component attributes to central function and store in separate folder * prepare: sort imports and remove six dependency * prepare: remove add_emission_prices * prepare: remove unused set_line_s_max_pu This is a function from prepare_network * prepare: remove unused set_line_volume_limit This is a PyPSA-Eur function from prepare_network * prepare: tidy add_co2limit * remove six dependency * prepare: tidy code first batch * prepare: extend override_component_attrs to avoid hacky madd * prepare: remove hacky madd() for individual components * prepare: tidy shift function * prepare: nodes and countries from n.buses not pop_layout * prepare: tidy loading of pop_layout * prepare: fix prepare_costs function * prepare: optimise loading of traffic data * prepare: move localizer into generate_periodic profiles * prepare: some formatting of transport data * prepare: eliminate some code duplication * prepare: fix remove_h2_network - only try to remove EU H2 store if it exists - remove readding nodal Stores because they are never removed * prepare: move cost adjustment to own function * prepare: fix a syntax error * prepare: add investment_year to get() assuming global variable * prepare: move co2_totals out of prepare_data() * Snakefile: remove unused prepare_sector_network inputs * prepare: move limit p/s_nom of lines/links into function * prepare: tidy add_co2limit file handling * Snakefile: fix tabs * override_component_attrs: add n/a defaults * README: Add network picture to make scope clear * README: Fix date of preprint (was too optimistic...) * prepare: move some more config options to config.yaml * prepare: runtime bugfixes * fix benchmark path * adjust plot ylims * add unit attribute to bus, correct cement capture efficiency * bugfix: land usage constrained missed inplace operation Co-authored-by: Tom Brown <tom@nworbmot.org> * add release notes * remove old fix_branches() function * deps: make geopy optional, remove unused imports * increase default BarConvTol * get ready for upcoming PyPSA release * re-remove ** bug * amend release notes Co-authored-by: Tom Brown <tom@nworbmot.org>
53 lines
1.6 KiB
Python
53 lines
1.6 KiB
Python
"""Build solar thermal collector time series."""
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import geopandas as gpd
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import atlite
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import pandas as pd
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import xarray as xr
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import numpy as np
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if __name__ == '__main__':
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if 'snakemake' not in globals():
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from helper import mock_snakemake
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snakemake = mock_snakemake(
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'build_solar_thermal_profiles',
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simpl='',
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clusters=48,
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)
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if 'snakemake' not in globals():
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from vresutils import Dict
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import yaml
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snakemake = Dict()
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with open('config.yaml') as f:
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snakemake.config = yaml.safe_load(f)
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snakemake.input = Dict()
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snakemake.output = Dict()
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config = snakemake.config['solar_thermal']
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time = pd.date_range(freq='h', **snakemake.config['snapshots'])
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cutout_config = snakemake.config['atlite']['cutout']
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cutout = atlite.Cutout(cutout_config).sel(time=time)
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clustered_regions = gpd.read_file(
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snakemake.input.regions_onshore).set_index('name').buffer(0).squeeze()
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I = cutout.indicatormatrix(clustered_regions)
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for area in ["total", "rural", "urban"]:
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pop_layout = xr.open_dataarray(snakemake.input[f'pop_layout_{area}'])
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stacked_pop = pop_layout.stack(spatial=('y', 'x'))
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M = I.T.dot(np.diag(I.dot(stacked_pop)))
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nonzero_sum = M.sum(axis=0, keepdims=True)
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nonzero_sum[nonzero_sum == 0.] = 1.
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M_tilde = M / nonzero_sum
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solar_thermal = cutout.solar_thermal(**config, matrix=M_tilde.T,
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index=clustered_regions.index)
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solar_thermal.to_netcdf(snakemake.output[f"solar_thermal_{area}"])
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