Configuration

run

It is common conduct to analyse 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 run section is used for running and storing scenarios with different configurations which are not covered by wildcards. It determines the path at which resources, networks and results are stored. Therefore the user can run different configurations within the same directory.

run:
  name: "Default" # use this to keep track of runs with different settings
  disable_progressbar: false # set to true to disable the progressbar
  shared_resources: false # set to true to share the default resources across runs
  shared_cutouts: true # set to true to share the default cutout(s) across runs
  validation: false # set to true to run back-casting plots

	Unit	Values	Description
name	–	any string	Specify a name for your run. Results will be stored under this name.
disable_progrssbar	bool	{true, false}	Switch to select whether progressbar should be disabled.
shared_resources	bool	{true, false}	Switch to select whether resources should be shared across runs.
shared_cutouts	bool	{true, false}	Switch to select whether cutouts should be shared across runs.
validation	bool	{true, false}	Switch to enable back-casting validation plotting

scenario

The scenario section is used for setting the wildcards and defining planning horizon settings. All configurations within this section are described in wildcards with the exception of planning_horizons and foresight.

Planning horizons determines which year of future demand forecast to use for your planning model. If you leave planning_horizons: empty, historical demand will be set according to snapshots.

scenario:
  interconnect: [western] #"usa|texas|western|eastern"
  clusters: [80]
  opts: [Ep-Co2L0.2]
  ll: [v1.0]
  scope: "total" # "urban", "rural", or "total"
  sector: "" # G
  planning_horizons:
  - 2030    #(2030, 2040, 2050)

foresight:  # Only Single Stage Currently

	Unit	Values	Description
planning_horizons	int	(2018-2023, 2030, 2040, 2050)	Specifies the year of demand data to use. Historical values will use EIA930 data, Future years will use NREL EFS data.
foresight	bool	{true, false}	Not implemented (placeholder)

snapshots

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

snapshots:
  start: "2019-01-01"
  end: "2020-01-01"
  inclusive: "left"

	Unit	Values	Description
start	–	str or datetime-like; e.g. YYYY-MM-DD	Left bound of date range
end	–	str or datetime-like; e.g. YYYY-MM-DD	Right bound of date range
inclusive	–	One of {‘neither’, ‘both’, ‘left’, ‘right’}	Make the time interval closed to the left, right, or both sides both or neither side None.

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

atlite:
  default_cutout: era5_2019
  nprocesses: 8
  show_progress: false # false saves time
  cutouts:
    era5_2019:
      module: era5 # in priority order
      time: ['2019', '2019']
  interconnects:
    western:
      x: [-126, -99]
      y: [27, 50]
      dx: 0.3
      dy: 0.3
    eastern:
      x: [-109, -65]
      y: [23, 50]
      dx: 0.3
      dy: 0.3
    texas:
      x: [-110, -90]
      y: [24, 37]
      dx: 0.3
      dy: 0.3
    usa:
      x: [-126, -65]
      y: [23, 50]
      dx: 0.3
      dy: 0.3

	Unit	Values	Description
default_cutout	–	str	Defines a default cutout.
nprocesses	–	int	Number of parallel processes in cutout preparation
show_progress	bool	true/false	Whether progressbar for atlite conversion processes should be shown. False saves time.
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.
– – dx	°	Larger than 0.25	Grid resolution for longitude
– – dy	°	Larger than 0.25	Grid resolution for latitude
– – 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.

electricity

Specifies the types of generators that are included in the network, which are extendable, and the CO2 base for which the optimized reduction is relative to.

electricity:
  conventional_carriers: [nuclear, oil, OCGT, CCGT, coal, geothermal, biomass] # Choose the conventional plant types to include in network
  renewable_carriers: [onwind, offwind, offwind_floating, solar, hydro] # Choose the renewable plant types to include in network
  voltage_simplified: 230 #Voltage level to simplify network to in rule "simplify network"
  co2limit: 1.4728e+9 # 0.8 * 1.841e+9
  co2limit_enable: false # For sector coupled studies
  co2base: 226.86e+6 #base_from_2020 Locations of the 250 MMmt of CO2 emissions from the WECC 2021.
  gaslimit: false # global gas usage limit of X MWh_th
  gaslimit_enable: false # For sector coupled studies
  retirement: economic # "economic" or "technical"
  SAFE_reservemargin: 0.14
  regional_Co2_limits: 'config/policy_constraints/regional_Co2_limits.csv'
  agg_p_nom_limits: 'config/policy_constraints/agg_p_nom_minmax.csv'
  portfolio_standards: 'config/policy_constraints/portfolio_standards.csv'
  SAFE_regional_reservemargins: 'config/policy_constraints/SAFE_regional_prm.csv'
  transmission_interface_limits: 'config/policy_constraints/transmission_interface_limits.csv'


  operational_reserve:
    activate: false
    epsilon_load: 0.02
    epsilon_vres: 0.02
    contingency: 4000

  max_hours:
    battery: 6
    H2: 168

  extendable_carriers:
    Generator: [solar, onwind, offwind, offwind_floating, OCGT, CCGT, coal] #offwind, offwind_floating,
    StorageUnit: [4hr_battery_storage] # [Xhr-battery-storage (2-10 hours)]
    Store: []
    Link: [] 

  demand: 
    profile: efs # efs, eia
    scale: 1 # efs, aeo, or a number 
    disaggregation: pop # pop
    scenario: 
      efs_case: reference # reference, medium, high
      efs_speed: moderate # slow, moderate, rapid
      aeo: reference

  autarky:
    enable: false
    by_country: false

	Unit	Values	Description
conventional_carriers	–	Any subset of {nuclear, oil, OCGT, CCGT, coal, 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.
voltage_simplified	kV	int	Voltage level to simplify network to in rule simplify_network
gaslimit	MWhth	float or false	Global gas usage limit (Set False for development)
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.
retirement	–	One of economic or technical	Sets the retirement method for converntional generators. If technical all generators p_nom_min are set to p_nom to prevent selling off of the asset. Retirements are then tracked in post-proccessing. If economic existing plants have their p_nom_min set as 0, p_nom_max set to p_nom, and capital costs set to fixed costs. Generators with p_nom are then added to handle capacity expansion.”
operational_reserve:			Settings for reserve requirements following 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.
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.
Storage Unit	–	Any subset of {battery}	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}	Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity.
Links	–	Any subset of {}	Adds extendable linksat 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.
demand:
–profile	–	One of {efs, eia}	Datasource for electrical load data. EFS pulls future state level electrical demand data. EIA pulls historical balancing level electrical demand dataa.
–scale	–	One of {efs, aeo}, or a float	(UNDER DEVELOPMENT) Used to scale the demand profile data. AEO will scale according to demand projections from the Annual Energy Outlook. EFS will scale according to growth rates from the Electrification Futures Study. Or can sclae according to a user defined value.
–disaggregation	–	One of {pop}	Method to dissagreagate load data. pop will dissagregate based on population from Breakthrough Energy.
scenario:
–efs_case	–	One of {reference, medium, high}	(UNDER DEVELOPMENT) Extracts EFS data according to level of adoption
–efs_speed	–	One of {slow, moderate, fast}	(UNDER DEVELOPMENT) Extracts EFS data according to speed of electrification
–aeo	–	One of the AEO scenarios here	(UNDER DEVELOPMENT) Scales future demand according to the AEO scenario
autarky
–enable	bool	true or false	Require each node to be autarkic by removing all lines and links.
–by_country	bool	true or false	Require each region to be autarkic by removing all cross-border lines and links. electricity: autarky must be enabled.

Note

See here for information on interconnect level base emission values.

renewable

solar

  solar:
    cutout: era5_2019
    resource:
      method: pv
      panel: CSi
      orientation: latitude_optimal # will lead into optimal
    capacity_per_sqkm: 4.6 # From 1.7 to 4.6 addresses issue #361 - TODO revisit this assumption
    correction_factor: 1 # 0.854337
    corine:
      grid_codes: [20, 30, 40, 60, 90, 100] #see above for codes
    natura: true
    cec: true
    potential: conservative # simple or conservative
    clip_p_max_pu: 1.e-2
    extendable: true

	Unit	Values	Description
cutout	–	Should be a folder listed in the configuration atlite: cutouts: (e.g. ‘{interconnect}-2019-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 Copornicus Land Cover code list (see assumptions).	Specifies areas according to Land Cover codes which are generally eligible for wind turbine placement.
natura	bool	{true, false}	Switch to exclude Protected Planet natural protection areas. Area is excluded if true.
potential	–	One of {‘simple’, ‘conservative’}	Method to compute the maximal installable potential for a node; confer Rule build_renewable_profiles
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.
excluder_resolution	m	float	Resolution on which to perform geographical elibility analysis.

onwind

  onwind:
    cutout: era5_2019
    resource:
      method: wind
      turbine: Vestas_V112_3MW
      add_cutout_windspeed: true
    capacity_per_sqkm: 3 # conservative, ScholzPhd Tab 4.3.1: 10MW/km^2
    correction_factor: 1 # 0.93
    corine:
      #all keys labeled corrine are actually copernicus codes. Using the name corrine bc using the pypsa-eur convention: https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS1_PUM_LC100m-V3_I3.4.pdf
      grid_codes: [20, 30, 40, 60, 100, 112, 113, 114, 115]
      distance: 10 #buffer from distance_grid_codes that are to be excluded
      distance_grid_codes: [50]
    natura: true
    cec: true
    potential: conservative # simple or conservative
    clip_p_max_pu: 1.e-2
    extendable: true

	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 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)[PyPSA/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 Copornicus Land Cover code list (see assumptions).	Specifies areas according to 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 Copornicus Land Cover code list (see assumptions).	Specifies areas according to Land Cover codes which are generally eligible for wind turbine placement.
natura	bool	{true, false}	Switch to exclude Protected Planet natural protection areas. Area is excluded if true.
potential	–	One of {‘simple’, ‘conservative’}	Method to compute the maximal installable potential for a node; confer Rule build_renewable_profiles
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.
correction_factor	–	float	Correction factor for capacity factor time series.

Offshore wind

  offwind:
    cutout: era5_2019
    resource:
      method: wind
      turbine: NREL_ReferenceTurbine_2020ATB_5.5MW
      # add_cutout_windspeed: true
    capacity_per_sqkm: 3 # 2021–2022 Transmission Plan, CAISO
    correction_factor: 1 # 0.8855 # proxy for wake losses, from 10.1016/j.energy.2018.08.153
    corine:
      grid_codes: [80, 200] #page 28 of https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS1_PUM_LC100m-V3_I3.4.pdf
    natura: true
    boem_screen: true
    max_depth: 60 # meters, ref https://www.nrel.gov/docs/fy16osti/66599.pdf
    min_shore_distance: 22000 # meters
    max_shore_distance: 65000 # meters
    potential: conservative # simple or conservative
    clip_p_max_pu: 1.e-2
    extendable: true
  offwind_floating:
    cutout: era5_2019
    resource:
      method: wind
      turbine: NREL_ReferenceTurbine_2020ATB_15MW_offshore
      add_cutout_windspeed: true
    capacity_per_sqkm: 3 # 2021–2022 Transmission Plan, CAISO
    correction_factor: 1 # 0.8855 # proxy for wake losses, from 10.1016/j.energy.2018.08.153
    corine:
      grid_codes: [80, 200] #page 28 of https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS1_PUM_LC100m-V3_I3.4.pdf
    natura: true
    boem_screen: true
    min_depth: 60 # meters, ref https://www.nrel.gov/docs/fy16osti/66599.pdf
    max_depth: 1300 # meters, ref https://www.nrel.gov/docs/fy22osti/83650.pdf
    min_shore_distance: 22000 # meters
    max_shore_distance: 65000 # meters
    potential: conservative # simple or conservative
    clip_p_max_pu: 1.e-2
    extendable: true

lines

lines:
  types: # All temporary values, need to be updated
    115.: "Al/St 240/40 2-bundle 220.0"
    138.: "Al/St 240/40 2-bundle 220.0"
    161.: "Al/St 240/40 2-bundle 220.0"
    230.: "Al/St 240/40 2-bundle 220.0"
    345.: "Al/St 240/40 4-bundle 380.0"
    500.: "Al/St 560/50 4-bundle 750.0"
    765.: "Al/St 560/50 4-bundle 750.0"
  s_max_pu: 0.7
  s_nom_max: .inf
  max_extension: 1000.0e+3
  length_factor: 1.25
  interface_transmission_limits: true

	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 TAMU Network.
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.
max_extension	MW	float	Upper limit for the extended 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.
interface_transmission_limits	–	true or false	Activate the Interface Transmission Limits (ITL) zones limits.

links

links:
  p_max_pu: 1.0
  p_nom_max: .inf
  max_extension: 1000.0e+3

	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.
max_extension	MW	float	Upper limit for the extended capacity of each extendable line.

costs

costs:  # based on the potentials, assuming  (0.1 kW/m2 and 10 m2/person)
  year: 2030
  version: v0.6.0
  rooftop_share: 0.0
  ng_fuel_year: 2019 # year of the natural gas price from CAISO [2019- 2023]
  fill_values:
    FOM: 0
    VOM: 0
    efficiency: 1
    fuel: 0
    investment: 0
    lifetime: 25
    "CO2 intensity": 0
    "discount rate": 0.07
  marginal_cost:
    solar: 0.00
    onwind: 0.00
    offwind: 0.00
    hydro: 0.
    H2: 0.
    electrolysis: 0.
    fuel cell: 0.
    battery: 0.
    battery inverter: 0.
  emission_prices: # in currency per tonne emission, only used with the option Ep
    enable: false
    co2: 0.
    co2_monthly_prices: false

	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. v0.5.0	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	$/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	$/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.
– enable	bool	true or false	Add cost for a carbon-dioxide price configured in costs: emission_prices: co2 to marginal_cost of generators (other emission types listed in network.carriers possible as well)
– co2	$/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 :mod:prepare_network.

sector

Warning

Sector coupling studies are all under active development

sector:
  co2_sequestration_potential: 0
  natural_gas:
    allow_imports_exports: true # false to be implemented
    cyclic_storage: false
  heating:
    heat_pump_sink_T: 55.
  demand:
    profile:
      residential: eulp # efs, eulp
      commercial: eulp # efs, eulp
      transport: efs # efs
      industry: efs # efs
    scale:
      residential: aeo # efs, aeo
      commercial: aeo # efs, aeo
      transport: aeo # efs, aeo
      industry: aeo # efs, aeo
    disaggregation:
      residential: pop # pop
      commercial: pop # pop
      transport: pop # pop
      industry: pop # pop
    scenarios:
      aeo: reference

	Unit	Values	Description
co2_sequestration_potential	MtCO2/a	float	The potential of sequestering CO2 in the spatial scope per year
natural_gas			Options when implementing natural gas network with sector wildcard ‘G’
– allow_imports_exports	bool	{true, false}	Allow international imports/exports
– cyclic_storage	bool	{true, false}	Apply cyclic storage constraints on linepack and underground storage
heating			Options when implementing heating network with sector wildcard ‘H’
– heat_pump_sink_T	C	float	The temperature heat sink used in heat pumps based on DTU / large area radiators. The value is conservatively high to cover hot water and space heating in poorly-insulated buildings
demand:			Demand configuration options for each end use sector
profile:			Demand profile source. EFS pulls future state level electrical demand data. eulp pulls End Use Load Profiles for 2018.”
–residential	–	One of {efs, eulp}	Datasource for residential electrical and cooling and heating data.
–commercial	–	One of {efs, eulp}	Datasource for commercial electrical and cooling and heating data.
–transport	–	One of {efs}	Datasource for transportation electrical data.
–industry	–	One of {efs}	Datasource for industrial electrical data.
scale:			Scales data. AEO will scale according to demand projections from the Annual Energy Outlook. EFS will scale according to growth rates from the Electrification Futures Study. Or can scale according to a user defined value.
–residential	–	One of {efs, aeo}, or a float	(UNDER DEVELOPMENT) Used to scale residential demand profile data.
–commercial	–	One of {efs, aeo}, or a float	(UNDER DEVELOPMENT) Used to scale commercial demand profile data.
–transport	–	One of {efs, aeo}, or a float	(UNDER DEVELOPMENT) Used to scale transport demand profile data.
–industry	–	One of {efs, aeo}, or a float	(UNDER DEVELOPMENT) Used to scale industrial demand profile data.
disaggregation:			Dissagregation method. pop will dissagregate based on population from Breakthrough Energy.
–residential	–	One of {pop}	Method to dissagreagate residential load data.
–commercial	–	One of {pop}	Method to dissagreagate commercial load data.
–transport	–	One of {pop}	Method to dissagreagate transport load data.
–industry	–	One of {pop}	Method to dissagreagate industrial load data.
scenario:
–efs_case	–	One of {reference, medium, high}	(UNDER DEVELOPMENT) Extracts EFS data according to level of adoption
–efs_speed	–	One of {slow, moderate, fast}	(UNDER DEVELOPMENT) Extracts EFS data according to speed of electrification
–aeo	–	One of the AEO scenarios here	(UNDER DEVELOPMENT) Scales future demand according to the AEO scenario

clustering

When clustering aggregation_zones defines the region boundaries which will be respected through the clustering process; State boarders, balancing authority regions, or REeDs shapes. This feature is important for imposing constraints (opts) which are defined over specific regions. For example, the data included in the model on interface transfer capacities are prepared for REeDs shapes but not states and BA regions. Moving forward we plan to use REeDs shapes as our default however we will maintain States and BA regions as well.

Each clustering and interconnection option will have a different number of minimum nodes which can be clustered to, an error will be thrown in cluster_network notifying you of that number if you have selected a value too low.

Cleaned and labeled REeDs Shapes are pulled from this github repository: https://github.com/pandaanson/NYU-law-work

clustering:
  simplify_network:
    to_substations: false # network is simplified to nodes with positive or negative power injection (i.e. substations or offwind connections)
    algorithm: kmeans # choose from: [hac, kmeans]
    feature: solar+onwind-time # only for hac. choose from: [solar+onwind-time, solar+onwind-cap, solar-time, solar-cap, solar+offwind-cap] etc.
  cluster_network:
    algorithm: kmeans # choose from: [hac, kmeans]
    feature: solar+onwind-time
    aggregation_zones: 'reeds_zone' # [balancing_area, state, reeds_zone]
    exclude_carriers: []
    consider_efficiency_classes: false
  aggregation_strategies:
    generators:
      committable: any
      ramp_limit_up: max
      ramp_limit_down: max
      vom_cost: mean
      fuel_cost: mean
      heat_rate: mean
  temporal:
    resolution_elec: false
    resolution_sector: false

focus_weights:
  # California: 0.5

	Unit	Value	Description
simplify_network:
to_substations	bool	{true, false}	Implementation curerntly overrides to true. Network is simplified to substation nodes with positive or negative power injection.
algorithm	str	{‘kmeans’}
feature	str	{‘solar+onwind-time’, ‘solar+onwind-cap’, ‘solar-time’, ‘solar-cap’, ‘solar+offwind-cap’}	For HAC clustering.
cluster_network:
algorithm	str	{‘kmeans’}
feature	str	{‘solar+onwind-time’, ‘solar+onwind-cap’, ‘solar-time’, ‘solar-cap’, ‘solar+offwind-cap’}	For HAC clustering.
aggregation_zones	str	{‘balancing_area’, ‘state’, ‘reeds_zone’}	Boundaries of GIS shapes that are to be respected in clustering. Retain if you would like to analyze expansion within a given zone.
aggregation_strategies:
table –> {key}	str	{‘mean’,’max’,’min’,etc}	Specifiy the method of aggregating fields within the generators, buses tables.
focus_weights:
region_name’	float		Specify the proportion of nodes to be attributed to a given zone in the form (California: 0.5) for half of all nodes to be located in California

Note

feature: in simplify_network: are only relevant if hac were chosen in algorithm.

Tip

use min in p_nom_max: for more conservative assumptions.

solving

solving:
  #tmpdir: "path/to/tmp"
  options:
    load_shedding: false
    clip_p_max_pu: 1.e-2
    noisy_costs: true
    skip_iterations: true
    rolling_horizon: false
    seed: 123
    # options that go into the optimize function
    track_iterations: false
    min_iterations: 4
    max_iterations: 6
    transmission_losses: 2
    linearized_unit_commitment: true
    horizon: 8760
    assign_all_duals: true


  solver:
    name: gurobi
    options: gurobi-default

  solver_options:
    highs-default:
      # refer to https://ergo-code.github.io/HiGHS/options/definitions.html#solver
      threads: 4
      solver: "ipm"
      run_crossover: "off"
      small_matrix_value: 1e-6
      large_matrix_value: 1e9
      primal_feasibility_tolerance: 1e-5
      dual_feasibility_tolerance: 1e-5
      ipm_optimality_tolerance: 1e-4
      parallel: "on"
      random_seed: 123
    gurobi-default:
      threads: 8
      method: 2 # barrier
      crossover: 0
      BarConvTol: 1.e-4
      OptimalityTol: 1.e-4
      FeasibilityTol: 1.e-3
      Seed: 123
      AggFill: 0
      PreDual: 0
      GURO_PAR_BARDENSETHRESH: 200
    gurobi-numeric-focus:
      name: gurobi
      NumericFocus: 3       # Favour numeric stability over speed
      method: 2             # barrier
      crossover: 0          # do not use crossover
      BarHomogeneous: 1     # Use homogeneous barrier if standard does not converge
      BarConvTol: 1.e-5
      FeasibilityTol: 1.e-4
      OptimalityTol: 1.e-4
      ObjScale: -0.5
      threads: 8
      Seed: 123
    gurobi-fallback:        # Use gurobi defaults
      name: gurobi
      crossover: 0
      method: 2             # barrier
      BarHomogeneous: 1     # Use homogeneous barrier if standard does not converge
      BarConvTol: 1.e-5
      FeasibilityTol: 1.e-5
      OptimalityTol: 1.e-5
      Seed: 123
      threads: 8
    cplex-default:
      threads: 4
      lpmethod: 4 # barrier
      solutiontype: 2 # non basic solution, ie no crossover
      barrier.convergetol: 1.e-5
      feasopt.tolerance: 1.e-6
    cbc-default: {} # Used in CI
    glpk-default: {} # Used in CI

  mem: 30000 #memory in MB; 20 GB enough for 50+B+I+H2; 100 GB for 181+B+I+H2
  walltime: "12:00:00"

	Unit	Values	Description
options
=– operations_only	bool	{‘true’,’false’}	Overrides p_nom_extendible for other configurations and forces solution of operations only simulations. Use with co2 opt limit 1.0.
=– load_shedding	bool/float	{‘true’,’false’, float}	Add generators with very high marginal cost to simulate load shedding and avoid problem infeasibilities. If load shedding is a float, it denotes the marginal cost in $/kWh.
=– 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.
=– 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 \(\mathcal{U}(0.09,0,11)\).
=– skip_iterations	bool	{‘true’,’false’}	Skip iterating, do not update impedances of branches. Defaults to true.
=– rolling_horizon	bool	{‘true’,’false’}	Whether to optimize the network in a rolling horizon manner, where the snapshot range is split into slices of size horizon which are solved consecutively.
=– seed	int		Random seed for increased deterministic behaviour.
=– 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)
=– 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.
=– transmission_losses	int	[0-9]	Add piecewise linear approximation of transmission losses based on n tangents. Defaults to 0, which means losses are ignored.
=– linearized_unit_commitment	bool	{‘true’,’false’}	Whether to optimise using the linearized unit commitment formulation.
=– horizon	int		Number of snapshots to consider in each iteration. Defaults to 100.
solver
=– 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.
=– options	–		Name of solver_options to use from dictionary below.
solver_options		dict	Dictionary of pre-fixed solver options
mem	MB	int	Estimated maximum memory requirement for solving networks.

plotting

plotting:
  costs_max: 800
  costs_threshold: 1

  energy_max: 15000.
  energy_min: -10000.
  energy_threshold: 50.

  # vre_techs: ["onwind","offwind_floating", "offwind-ac", "offwind-dc", "solar", "ror"]
  # conv_techs: ["OCGT", "CCGT", "Nuclear", "Coal"]
  # storage_techs: ["hydro+PHS", "battery", "H2"]
  # load_carriers: ["AC load"]
  # AC_carriers: ["AC line", "AC transformer"]
  # link_carriers: ["DC line", "Converter AC-DC"]
  tech_colors:
    "onwind": "#235ebc"
    "wind": "#235ebc"
    "onshore wind": "#235ebc"
    'offwind': "#dd6895"
    'offshore wind': "#6895dd"
    'offwind-ac': "#6895dd"
    'offshore wind ac': "#6895dd"
    'offwind-dc': "#74c6f2"
    'offshore wind dc': "#74c6f2"
    'offwind_floating': "#11a1c1"
    "hydro": "#08ad97"
    "hydro+PHS": "#08ad97"
    "PHS": "#08ad97"
    "hydro reservoir": "#08ad97"
    'hydroelectricity': '#08ad97'
    "ror": "#4adbc8"
    "run of river": "#4adbc8"
    'solar': "#f9d002"
    'solar PV': "#f9d002"
    'solar thermal': '#ffef60'
    'biomass': '#0c6013'
    'solid biomass': '#06540d'
    'biogas': '#23932d'
    'waste': '#68896b'
    'geothermal': '#ba91b1'
    "OCGT": "#d35050"
    "gas": "#d35050"
    "ng": "#d35050"
    "natural gas": "#d35050"
    "CCGT": "#b20101"
    "nuclear": "#ff9000"
    "coal": "#707070"
    "lignite": "#9e5a01"
    "oil": "#262626"
    "H2": "#ea048a"
    "hydrogen storage": "#ea048a"
    "battery": "#b8ea04"
    "2hr_battery_storage": "#aee000"
    "4hr_battery_storage": "#a4d600"
    "6hr_battery_storage": "#9acc00"
    "8hr_battery_storage": "#90c200"
    "10hr_battery_storage": "#86b800"
    "Electric load": "#f9d002"
    "electricity": "#f9d002"
    "lines": "#70af1d"
    "transmission lines": "#70af1d"
    "AC-AC": "#70af1d"
    "AC line": "#70af1d"
    "AC": "#70af1d"
    "links": "#8a1caf"
    "HVDC links": "#8a1caf"
    "DC-DC": "#8a1caf"
    "DC link": "#8a1caf"
    "DC": "#8a1caf"
    "Load": "#2ad55f"

  nice_names:
    OCGT: "Open-Cycle Gas"
    CCGT: "Combined-Cycle Gas"
    offwind: "Fixed Bottom Offshore Wind"
    offwind_floating: "Floating Offshore Wind"
    onwind: "Onshore Wind"
    solar: "Solar"
    PHS: "Pumped Hydro Storage"
    hydro: "Reservoir & Dam"
    battery: "Battery Storage"
    H2: "Hydrogen Storage"
    lines: "Transmission Lines"
    ror: "Run of River"
    Load: "Load Shed"

	Unit	Values	Description
map
– boundaries	°	[x1,x2,y1,y2]	Boundaries of the map plots in degrees latitude (y) and longitude (x)
costs_max	bn $o	float	Upper y-axis limit in cost bar plots.
costs_threshold	bn $o	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](https://en.wikipedia.org/wiki/Web_colors#Hex_triplet)).
nice_names	–	str -> str	Mapping from network carrier to a more readable name.