* 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>
Previously, the transformation of the Steel and Aluminum production was assumed to occur overnight.
This commit enables the definition of a transformation path via the config.yaml file.
This requires adding the {planning_horizon} to the input and output file name of the following rules:
build_industrial_production_per_country_tomorrow
build_industrial_production_per_node
build_industry_energy_demand_per_node
prepare_sector_network
When plotting the balance for H2, the rename dictionary merges all the demands containing H2.
This commit disables such merging and keeps different colours for H2 in shipping and H2 in industry. This is useful when one wants to look at the H2 balance and have an overview of where the H2 is consumed in the model.
The share of shipping demand that is transformed is defined now for different years to be used with the myopic code.
The carbon emission from the remaining share is treated as a negative load on the atmospheric carbon dioxide bus, just like aviation and land transport emissions.
Fixing that the code stops with an error if running without the industry sector, e.g. only including electricity and heat. When the industry sector is not included, balances_df.index.levels[0] does not include "process emissions". Using the XOR operator "^" does then add it instead of removing it when compared to the co2_carriers list. The XOR operator does only work as intended, i.e. excluding the three emission-related strings, when these strings are already in the original list. The proposed change fixes the issue.
* Make code more readable; remove misleading function arguments and add necessary ones
* Update scripts/build_energy_totals.py
Co-authored-by: Fabian Neumann <fabian.neumann@outlook.de>
Recently ICE vehicles were added, but the emissions were not accounted
for. Now, like aviation emissions, they are added as a negative load
to the "co2 atmosphere" bus.
The heat output from the carbon capture (CC) was being subtracted from
the CHP rather than the heat input.
Since the heat output and heat input are the same in the DEA
technology database (but at different temperatures), this bug has no
consequence, but still better to correct it.
Reasoning: we can also have fossil and biomass liquid hydrocarbons, as
well as production from the Fischer-Tropsch process, particularly for
simulations before 2050.
For the myopic method, based on the carbon budget indicated in the config file (sector_opts), a CO2 limit is calculated for every planning_horizon following an exponential or beta decay. A file with CO2 limit in every planning_horizon and a plot showing historical and planned CO2 emissions
are saved in the results
**This requires updating to UNFCCC_v23.csv in the data bundle**
This enables that the same function is used to read emissions in 2018, which are assumed to remain constant in 2019 and 2020 and subtracted from carbon budget (estimated from 2018 on).
I checked and 1990 emissions calculated with UNFCCC_v23 are very similar to those calculated with UNFCCC_v21 (<1% differences in all values at EU level).
Some countries show higher deviations, mainly in domestic aviation and navigation. I guess because those values started to be reported later and v23 should include more accurate values.
Running the rule solve_network in the university cluster, I was getting a "No space left on device" error. Making solve_dir=tmpdir by default avoids this error and makes it easier to identify any problem with temp files
This was breaking add_existing_baseyear.py and it is now fixed. Column name for commissioning year in powerplantmatching has changed. Now "DataIn" is used as column name, also when renewable capacities per country are added to the power plants dataframe
This is almost a direct copy PyPSA-Eur #167https://github.com/PyPSA/pypsa-eur/pull/167
A factor altering the maximum capacity (p_nom_max) can also be specified by e.g. solar+p3
One should be careful when using this for solar because the factor is applied to all the generators whose carrier includes the string 'solar' (i.e., it is applied to both utility and rooftop solar)
I would suggest implementing 'solar utility' and 'solar rooftop' as carriers, since this can be useful for other selecting processes. Is there is any reason for keeping 'solar' as a carrier for 'solar utility'?
The previous way of increasing maximum capacity via the config file (e.g 'solar3') is still present in the code.
For the myopic method, based on the carbon budget indicated in the config file (sector_opts), a CO2 limit is calculated for every planning_horizon following an exponential or beta decay. A file with CO2 limit in every planning_horizon and a plot showing historical and planned CO2 emissions
are saved in the results
**This requires updating to UNFCCC_v23.csv in the data bundle**
This enables that the same function is used to read emissions in 2018, which are assumed to remain constant in 2019 and 2020 and subtracted from carbon budget (estimated from 2018 on).
I checked and 1990 emissions calculated with UNFCCC_v23 are very similar to those calculated with UNFCCC_v21 (<1% differences in all values at EU level).
Some countries show higher deviations, mainly in domestic aviation and navigation. I guess because those values started to be reported later and v23 should include more accurate values.
Running the rule solve_network in the university cluster, I was getting a "No space left on device" error. Making solve_dir=tmpdir by default avoids this error and makes it easier to identify any problem with temp files
This was breaking add_existing_baseyear.py and it is now fixed. Column name for commissioning year in powerplantmatching has changed. Now "DataIn" is used as column name, also when renewable capacities per country are added to the power plants dataframe
Before it just had a fixed marginal cost. Now it uses DEA assumptions
for heat, electricity and capital costs.
This necessitates locating it somewhere concrete. Heat is taken from
urban central or decentral buses.
Use DEA assumptions for post-combustion carbon capture.
Also rename CCS as CC whenever only carbon capture is involved, since
sequestration (or CCU) is a separate step.
