* Update .gitignore
* Add fictitious load to account for non-transformed shipping emissions
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.
* Split colours for H2 in Industry and H2 in shipping when plotting balances.
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.
* Make transformation of Steel and Aluminum production depends on year
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
* small follow-up to merge
* Add oil consumed in shipping as a load to EU oil bus
* Update scripts/prepare_sector_network.py
* add planning_horizons wildcard to benchmark paths
* fixup: double fraction_primary for steel
Co-authored-by: Fabian Neumann <fabian.neumann@outlook.de>
* 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>
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.
* 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 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
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.
Only change was to remove the Store-Link-Bus combinations for
batteries and H2 storage from PyPSA-Eur, since they are implemented
with different names, costs and voltage level in PyPSA-Eur-Sec.
Removals are now done in a more transparent way in the config.yaml.
The assumptions for c_b and c_v and eta were arranged assuming
extraction plants (like the coal CHP in DEA).
However, if you look in DEA assumptions at "09b Wood Pellets Medium"
(used for solid biomass CHP) and "Gas turbine simple cycle (large)"
(used for gas CHP) they are not extraction plants but back pressure
plants.
The back pressure coefficient in DEA c_b is simply
c_b = name plate electricity efficiency / name plate heat efficiency
both measured when both heat and electricity are produced at maximum.
For the extraction plants, the efficiency was measured in condensation
mode, i.e. no heat production.
In almost 99.5% of cases the CHP dispatches along the backpressure
line where heat output is proportional to electricity output.
So we can switch to a single link to avoid the burden of modelling the
full electricity-heat feasibility space of CHPs.
This only applies to large CHPs in district heating networks.
Specify as dictionary, use get_parameter to get correct value.
Also remove old parameter "space_heating_fraction" since this is
superceded by the new exogenous retro code.
Strategy is too keep as much of configuration in config.yaml as
possible.
We also aim to allow exogenous investment-year-dependent
configurations to be done in a similar manner (e.g. share of district
heating or FCEV transport).
Since today's industrial electricity demand is distributed by
population and GDP, subtract this from the regular electricity demand
(which already has space/water heating subtracted).
Now regular electricity demand is only non-heating electricity demand
in residential and tertiary sectors.
Add back new industry electricity demand at the correct locations, as
determined using the hotmaps database.
I.e. when the generators are clustered to the "simplified" network
resolution, but the grid is clustered further, e.g. by using the
clusters = 37m "m" option.
I.e. when the generators are clustered to the "simplified" network
resolution, but the grid is clustered further, e.g. by using the
clusters = 37m "m" option.
Rather than taking a mean of the clustered connection costs.
Apply cost update also for overnight scenarios based on planning year.
Add land costs for onshore wind.
- add_brownfield.py: Have to make sure that for each CHP there is both
a heat and electric link, but they have different p_nom for each
CHP, so have to make sure we don't remove one without the other.
- solve_network.py: Make sure extra_functionality constraints for CHP
power-heat feasibility graph also work for non-extendable CHPs.
In order to calculate connection costs, average values for underground_fraction and average_distance are calculated for all the buses in the initial network mapped to the clustered network.
Previously they were distributed only by country to the first node in
the country.
Now conventional power plants are assigned to the correct node using
the bus map from PyPSA-Eur.
Wind and solar are distributed in each country by capacity factor.
The code has been refactored and a bug was fixed whereby total
capacities of wind and solar in each country were not correct.
Now the years in the config.yaml for myopic are integers not strings.
In prepare_costs, you need the min_count=1 in the sum so that it
generates NaNs for missing data (rather than 0) so that NaNs can be
subsituted by .fillna in the next line. Otherwise many values
(discount rates and efficiencies for solar, wind) are set to zero.
Also added carriers, storage and generators for coal, nuclear and
oil. (This needs to be organized better soon so that the carriers are
defined in config.yaml.)
* prepare_sector_network:
- add link for oil boiler in function add_industry()
- add function for partitioning clusters into different heat node types
* config.yaml: add option for oil_boiler
* costs.csv: add costs for oil boiler
Remove emissions from hydrogen production for ammonia (since H2 now
comes from electrolysis).
Allow process emissions from petrochemical production to be captured
(the carbon is not necessarily fossil, but could come from CCU).
All urban central (i.e. district heating) is aggregated to the same
profile and bus.
The code is now written to cycle over each heating sector to add
demand and supply technologies, only changing what is necessary to
change, rather than just copying chunks of code and modifying
parameters there. This should make it easier to get an overview of
what's going on.
These are specified in data/heat_load_profile.csv.
The resulting heat_demand df has MultiIndex columns, where the first
level is ["sector use"], and the second level level is nodes.
Because there was insufficient solid biomass in 3-4 countries to
supply industry for it locally, and we need to account for transport
of solid biomass.
Should be replaced by transport cost links between countries.
Heat buses renamed to:
rural (for low-density areas where district heating not possible)
urban decentral (for high-density areas without district heating and
individual heating technologies) (used to be called "urban")
urban central (for high-density areas with district heating) (used to
be called "central")
District heating losses applied only to urban central.
Before both initial SOC and final SOC were set to be zero, which
prevents synthetic fuel transfer over the year boundary, and prevents
the use of fossil fuels for non-zero CO2 scenarios.
Now done properly with cyclic Store (prevents accumulation of fossil
fuels as a form of sequestration) and Generator (to imitate fossil
fuel extraction).
tech name must only appear, but not be identical to generator
carrier. This allows to use the name "offshore" for both "offshore-ac"
and "offshore-dc", but then "solar" also catches "solar thermal",
which is fine since for solar thermal potentials are np.inf, unless
limit is 0 since np.inf*0 is nan.
Remove non-renewable generator and storage units from electricity-only
base network, since they're added differently here with links.
Remove unncessary cruft from config.yaml which is not used by
PyPSA-Eur-Sec (e.g. renewable configuration parameters).
Rename "naptha" to correct "naphtha".
