Configuration

PyPSA-RSA has several configuration options which are documented in this section and are collected in a config.yaml file located in the root directory. Users should copy the provided default configuration (config.default.yaml) and amend their own modifications and assumptions in the user-specific configuration file (config.yaml); confer installation instructions at Set Up the Default Configuration.

Top-level configuration

PyPSA-RSA imports the configuration options originally developed in PyPSA-Eur and here reported and adapted.

The options here described are collected in a config.yaml file located in the root directory. Users should copy the provided default configuration (config.default.yaml) and amend their own modifications and assumptions in the user-specific configuration file (config.yaml); confer installation instructions at Set Up the Default Configuration.

Note

Credits to PyPSA-Eur and PyPSA-meets-Earth developers for the initial drafting of the configuration documentation here reported

Top-level configuration

scenario

It is common conduct to analysis of energy system optimisation models for multiple scenarios for a variety of reasons, e.g. assessing their sensitivity towards changing the temporal and/or geographical resolution or investigating how investment changes as more ambitious greenhouse-gas emission reduction targets are applied.

The scenario section is an extraordinary section of the config file that is strongly connected to the Wildcards and is designed to facilitate running multiple scenarios through a single command

snakemake -j 1 solve_all_networks

For each wildcard, a list of values is provided. The rule solve_all_networks will trigger the rules for creating results/networks/solved_{model_file}_{regions}_{resarea}_l{ll}_{opts}.nc for all combinations of the provided wildcard values as defined by Python’s itertools.product(…) function that snakemake’s expand(…) function uses.

An exemplary dependency graph (starting from the simplification rules) then looks like this:

	Unit	Values	Description
resarea	–	cf. The {resarea} wildcard	List of {resarea} wildcards to run.
regions	–	cf. The {regions} wildcard	List of {regions} wildcards to run.
model_file	–	cf. The {model_file} wildcard	List of {model_file} wildcards to run.
ll	–	cf. The {ll} wildcard	List of {ll} wildcards to run.
opts	–	cf. The {opts} wildcard	List of {opts} wildcards to run.

snapshots- now specified in model_file.xlsx

Specifies the temporal range to build an energy system model for as arguments to pandas.date_range

electricity

	Unit	Values	Description
voltages	kV	Any subset of {220., 300., 380.}	Voltage levels to consider
gaslimit	MWhth	float or false	Global gas usage limit
co2limit	\(t_{CO_2-eq}/a\)	float	Cap on total annual system carbon dioxide emissions
co2base	\(t_{CO_2-eq}/a\)	float	Reference value of total annual system carbon dioxide emissions if relative emission reduction target is specified in {opts} wildcard.
agg_p_nom_limits	file	path	Reference to .csv file specifying per carrier generator nominal capacity constraints for individual countries if 'CCL' is in {opts} wildcard. Defaults to data/agg_p_nom_minmax.csv.
operational_reserve			Settings for reserve requirements following like GenX
– activate	bool	true or false	Whether to take operational reserve requirements into account during optimisation
– epsilon_load	–	float	share of total load
– epsilon_vres	–	float	share of total renewable supply
– contingency	MW	float	fixed reserve capacity
max_hours
– battery	h	float	Maximum state of charge capacity of the battery in terms of hours at full output capacity p_nom. Cf. PyPSA documentation.
– H2	h	float	Maximum state of charge capacity of the hydrogen storage in terms of hours at full output capacity p_nom. Cf. PyPSA documentation.
extendable_carriers
– Generator	–	Any extendable carrier	Defines existing or non-existing conventional and renewable power plants to be extendable during the optimization. Conventional generators can only be built/expanded where already existent today. If a listed conventional carrier is not included in the conventional_carriers list, the lower limit of the capacity expansion is set to 0.
– StorageUnit	–	Any subset of {‘battery’,’H2’}	Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity.
– Store	–	Any subset of {‘battery’,’H2’}	Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity.
– Link	–	Any subset of {‘H2 pipeline’}	Adds extendable links (H2 pipelines only) at every connection where there are lines or HVDC links without capacity limits and with zero initial capacity. Hydrogen pipelines require hydrogen storage to be modelled as Store.
powerplants_filter	–	use pandas.query strings here, e.g. Country not in [‘Germany’]	Filter query for the default powerplant database.
custom_powerplants	–	use pandas.query strings here, e.g. Country in [‘Germany’]	Filter query for the custom powerplant database.
conventional_carriers	–	Any subset of {nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass}	List of conventional power plants to include in the model from resources/powerplants.csv. If an included carrier is also listed in extendable_carriers, the capacity is taken as a lower bound.
renewable_carriers	–	Any subset of {solar, onwind, offwind-ac, offwind-dc, hydro}	List of renewable generators to include in the model.
estimate_renewable_capacities
– enable		bool	Activate routine to estimate renewable capacities
– from_opsd	–	bool	Add capacities from OPSD data
– year	–	bool	Renewable capacities are based on existing capacities reported by IRENA for the specified year
– expansion_limit	–	float or false	Artificially limit maximum capacities to factor * (IRENA capacities), i.e. 110% of <years>’s capacities => expansion_limit: 1.1 false: Use estimated renewable potentials determine by the workflow
– technology_mapping			Mapping between powerplantmatching and PyPSA-Eur technology names

Warning

Carriers in conventional_carriers must not also be in extendable_carriers.

atlite

Define and specify the atlite.Cutout used for calculating renewable potentials and time-series. All options except for features are directly used as cutout parameters.

	Unit	Values	Description
nprocesses	–	int	Number of parallel processes in cutout preparation
cutouts
– {name}	–	Convention is to name cutouts like <region>-<year>-<source> (e.g. europe-2013-era5).	Name of the cutout netcdf file. The user may specify multiple cutouts under configuration atlite: cutouts:. Reference is used in configuration renewable: {technology}: cutout:. The cutout base may be used to automatically calculate temporal and spatial bounds of the network.
– – module	–	Subset of {‘era5’,’sarah’}	Source of the reanalysis weather dataset (e.g. ERA5 or SARAH-2)
– – x	°	Float interval within [-180, 180]	Range of longitudes to download weather data for. If not defined, it defaults to the spatial bounds of all bus shapes.
– – y	°	Float interval within [-90, 90]	Range of latitudes to download weather data for. If not defined, it defaults to the spatial bounds of all bus shapes.
– – time		Time interval within [‘1979’, ‘2018’] (with valid pandas date time strings)	Time span to download weather data for. If not defined, it defaults to the time interval spanned by the snapshots.
– – features		String or list of strings with valid cutout features (‘inlfux’, ‘wind’).	When freshly building a cutout, retrieve data only for those features. If not defined, it defaults to all available features.

renewable

onwind

	Unit	Values	Description
cutout	–	Should be a folder listed in the configuration atlite: cutouts: (e.g. ‘RSA-2013-era5’) or reference an existing folder in the directory cutouts. Source module must be ERA5.	Specifies the directory where the relevant weather data ist stored.
resource
– method	–	Must be ‘wind’	A superordinate technology type.
– turbine	–	One of turbine types included in atlite	Specifies the turbine type and its characteristic power curve.
capacity_per_sqkm	\(MW/km^2\)	float	Allowable density of wind turbine placement.
corine
– grid_codes	–	Any subset of the CORINE Land Cover code list	Specifies areas according to CORINE Land Cover codes which are generally eligible for wind turbine placement.
– distance	m	float	Distance to keep from areas specified in distance_grid_codes
– distance_grid_codes	–	Any subset of the CORINE Land Cover code list	Specifies areas according to CORINE Land Cover codes to which wind turbines must maintain a distance specified in the setting distance.
natura	bool	{true, false}	Switch to exclude Natura 2000 natural protection areas. Area is excluded if true.
potential	–	One of {‘simple’, ‘conservative’}	Method to compute the maximal installable potential for a node; confer renewableprofiles
clip_p_max_pu	p.u.	float	To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero.

solar

	Unit	Values	Description
cutout	–	Should be a folder listed in the configuration atlite: cutouts: (e.g. ‘europe-2013-era5’) or reference an existing folder in the directory cutouts. Source module can be ERA5 or SARAH-2.	Specifies the directory where the relevant weather data ist stored that is specified at atlite/cutouts configuration. Both sarah and era5 work.
resource
– method	–	Must be ‘pv’	A superordinate technology type.
– panel	–	One of {‘Csi’, ‘CdTe’, ‘KANENA’} as defined in atlite	Specifies the solar panel technology and its characteristic attributes.
– orientation
– – slope	°	Realistically any angle in [0., 90.]	Specifies the tilt angle (or slope) of the solar panel. A slope of zero corresponds to the face of the panel aiming directly overhead. A positive tilt angle steers the panel towards the equator.
– – azimuth	°	Any angle in [0., 360.]	Specifies the azimuth orientation of the solar panel. South corresponds to 180.°.
capacity_per_sqkm	\(MW/km^2\)	float	Allowable density of solar panel placement.
correction_factor	–	float	A correction factor for the capacity factor (availability) time series.
corine	–	Any subset of the CORINE Land Cover code list	Specifies areas according to CORINE Land Cover codes which are generally eligible for solar panel placement.
natura	bool	{true, false}	Switch to exclude Natura 2000 natural protection areas. Area is excluded if true.
potential	–	One of {‘simple’, ‘conservative’}	Method to compute the maximal installable potential for a node; confer renewableprofiles
clip_p_max_pu	p.u.	float	To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero.

hydro

	Unit	Values	Description
cutout	–	Must be ‘RSA-2013-era5’	Specifies the directory where the relevant weather data ist stored.
carriers	–	Any subset of {‘ror’, ‘PHS’, ‘hydro’}	Specifies the types of hydro power plants to build per-unit availability time series for. ‘ror’ stands for run-of-river plants, ‘PHS’ represents pumped-hydro storage, and ‘hydro’ stands for hydroelectric dams.
PHS_max_hours	h	float	Maximum state of charge capacity of the pumped-hydro storage (PHS) in terms of hours at full output capacity p_nom. Cf. PyPSA documentation.
hydro_max_hours	h	Any of {float, ‘energy_capacity_totals_by_country’, ‘estimate_by_large_installations’}	Maximum state of charge capacity of the pumped-hydro storage (PHS) in terms of hours at full output capacity p_nom or heuristically determined. Cf. PyPSA documentation.
clip_min_inflow	MW	float	To avoid too small values in the inflow time series, values below this threshold are set to zero.

lines

	Unit	Values	Description
types	–	Values should specify a line type in PyPSA. Keys should specify the corresponding voltage level (e.g. 220., 300. and 380. kV)	Specifies line types to assume for the different voltage levels of the ENTSO-E grid extraction. Should normally handle voltage levels 220, 300, and 380 kV
s_max_pu	–	Value in [0.,1.]	Correction factor for line capacities (s_nom) to approximate \(N-1\) security and reserve capacity for reactive power flows
s_nom_max	MW	float	Global upper limit for the maximum capacity of each extendable line.
length_factor	–	float	Correction factor to account for the fact that buses are not connected by lines through air-line distance.
under_construction	–	One of {‘zero’: set capacity to zero, ‘remove’: remove completely, ‘keep’: keep with full capacity}	Specifies how to handle lines which are currently under construction.

links

	Unit	Values	Description
p_max_pu	–	Value in [0.,1.]	Correction factor for link capacities p_nom.
p_nom_max	MW	float	Global upper limit for the maximum capacity of each extendable DC link.
include_tyndp	bool	{‘true’, ‘false’}	Specifies whether to add HVDC link projects from the TYNDP 2018 which are at least in permitting.
under_construction	–	One of {‘zero’: set capacity to zero, ‘remove’: remove completely, ‘keep’: keep with full capacity}	Specifies how to handle lines which are currently under construction.

costs

	Unit	Values	Description
year	–	YYYY; e.g. ‘2030’	Year for which to retrieve cost assumptions of resources/costs.csv.
version	–	vX.X.X; e.g. ‘v0.1.0’	Version of technology-data repository to use.
rooftop_share	–	float	Share of rooftop PV when calculating capital cost of solar (joint rooftop and utility-scale PV).
fill_values	–	float	Default values if not specified for a technology in resources/costs.csv.
capital_cost	EUR/MW	Keys should be in the ‘technology’ column of resources/costs.csv. Values can be any float.	For the given technologies, assumptions about their capital investment costs are set to the corresponding value. Optional; overwrites cost assumptions from resources/costs.csv.
marginal_cost	EUR/MWh	Keys should be in the ‘technology’ column of resources/costs.csv. Values can be any float.	For the given technologies, assumptions about their marginal operating costs are set to the corresponding value. Optional; overwrites cost assumptions from resources/costs.csv.
emission_prices			Specify exogenous prices for emission types listed in network.carriers to marginal costs.
– co2	EUR/t	float	Exogenous price of carbon-dioxide added to the marginal costs of fossil-fuelled generators according to their carbon intensity. Added through the keyword Ep in the {opts} wildcard only in the rule prepare_network`.

Note

To change cost assumptions in more detail (i.e. other than marginal_cost and capital_cost), consider modifying cost assumptions directly in data/costs.csv as this is not yet supported through the config file. You can also build multiple different cost databases. Make a renamed copy of data/costs.csv (e.g. data/costs-optimistic.csv) and set the variable COSTS=data/costs-optimistic.csv in the Snakefile.

solving

options

	Unit	Values	Description
formulation	–	Any of {‘angles’, ‘kirchhoff’, ‘cycles’, ‘ptdf’}	Specifies which variant of linearized power flow formulations to use in the optimisation problem. Recommended is ‘kirchhoff’. Explained in this article.
load_shedding	bool	{‘true’,’false’}	Add generators with a prohibitively high marginal cost to simulate load shedding and avoid problem infeasibilities.
noisy_costs	bool	{‘true’,’false’}	Add random noise to marginal cost of generators by \(\mathcal{U}(0.009,0,011)\) and capital cost of lines and links by \(\mathcal{U}(0.09,0,11)\).
min_iterations	–	int	Minimum number of solving iterations in between which resistance and reactence (x/r) are updated for branches according to s_nom_opt of the previous run.
max_iterations	–	int	Maximum number of solving iterations in between which resistance and reactence (x/r) are updated for branches according to s_nom_opt of the previous run.
nhours	–	int	Specifies the \(n\) first snapshots to take into account. Must be less than the total number of snapshots. Rather recommended only for debugging.
clip_p_max_pu	p.u.	float	To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero.
skip_iterations	bool	{‘true’,’false’}	Skip iterating, do not update impedances of branches.
track_iterations	bool	{‘true’,’false’}	Flag whether to store the intermediate branch capacities and objective function values are recorded for each iteration in network.lines['s_nom_opt_X'] (where X labels the iteration)

solver

	Unit	Values	Description
name	–	One of {‘gurobi’, ‘cplex’, ‘cbc’, ‘glpk’, ‘ipopt’}; potentially more possible	Solver to use for optimisation problems in the workflow; e.g. clustering and linear optimal power flow.
opts	–	Parameter list for Gurobi and CPLEX	Solver specific parameter settings.

plotting

	Unit	Values	Description
map
– figsize	–	[width, height]; e.g. [7,7]	Figure size in inches.
– boundaries	°	[x1,x2,y1,y2]	Boundaries of the map plots in degrees latitude (y) and longitude (x)
– p_nom
– – bus_size_factor	–	float	Factor by which values determining bus sizes are scaled to fit well in the plot.
– – linewidth_factor	–	float	Factor by which values determining bus sizes are scaled to fit well in the plot.
costs_max	bn Euro	float	Upper y-axis limit in cost bar plots.
costs_threshold	bn Euro	float	Threshold below which technologies will not be shown in cost bar plots.
energy_max	TWh	float	Upper y-axis limit in energy bar plots.
energy_min	TWh	float	Lower y-axis limit in energy bar plots.
energy_threshold	TWh	float	Threshold below which technologies will not be shown in energy bar plots.
tech_colors	–	carrier -> HEX colour code	Mapping from network carrier to a colour (HEX colour code).
nice_names	–	str -> str	Mapping from network carrier to a more readable name.