Components#
PyPSA represents the power system using the following components:
component 
list_name 
description 
type 

Network 
networks 
Container for all components and functions which act upon the whole network. 

SubNetwork 
sub_networks 
Subsets of buses and passive branches (i.e. lines and transformers) that are connected (i.e. synchronous areas). 

Bus 
buses 
Electrically fundamental node where xport objects attach. 

Carrier 
carriers 
Energy carrier, such as AC, DC, heat, wind, PV or coal. Buses have direct carriers and Generators indicate their primary energy carriers. The Carrier can track properties relevant for global constraints, such as CO2 emissions. 

GlobalConstraint 
global_constraints 
Constraints for OPF that affect many components, such as CO2 emission constraints. 

Line 
lines 
Lines include distribution and transmission lines, overhead lines and cables. 
passive_branch 
LineType 
line_types 
Standard line types with per length values for impedances. 
standard_type 
Transformer 
transformers 
2winding transformer. 
passive_branch 
TransformerType 
transformer_types 
Standard 2winding transformer types. 
standard_type 
Link 
links 
Link between two buses with controllable active power  can be used for a transport power flow model OR as a simplified version of pointtopoint DC connection OR as a lossy energy converter. NB: for a lossless bidirectional HVDC or transport link, set p_min_pu = 1 and efficiency = 1. NB: It is assumed that the links neither produce nor consume reactive power. 
controllable_branch 
Load 
loads 
PQ power consumer. 
controllable_one_port 
Generator 
generators 
Power generator. 
controllable_one_port 
StorageUnit 
storage_units 
Storage unit with fixed nominalenergytonominalpower ratio. 
controllable_one_port 
Store 
stores 
Generic store, whose capacity may be optimised. 
controllable_one_port 
ShuntImpedance 
shunt_impedances 
Shunt y = g + jb. 
passive_one_port 
Shape 
shapes 
Geographical shapes of the network components. 
shape 
This table is also available as a dictionary within each network
object as network.components
.
For each class of components, the data describing the components is
stored in a pandas.DataFrame
corresponding to the
list_name
. For example, all static data for buses is stored in
network.buses
. In this pandas.DataFrame
the index corresponds
to the unique string names of the components, while the columns
correspond to the component static attributes. For example,
network.buses.v_nom
gives the nominal voltages of each bus.
Timevarying series attributes are stored in a dictionary of
pandas.DataFrame
based on the list_name
followed by _t
,
e.g. network.buses_t
. For example, the set points for the per unit
voltage magnitude at each bus for each snapshot can be found in
network.buses_t.v_mag_pu_set
. Please also read Timevarying data.
For each component class their attributes, their types
(float/boolean/string/int/series), their defaults, their descriptions
and their statuses are stored in a pandas.DataFrame
in the
dictionary network.components
as
e.g. network.components["Bus"]["attrs"]
. This data is reproduced
as tables for each component below.
Their status is either “Input” for those which the user specifies or “Output” for those results which PyPSA calculates.
The inputs can be either “required”, if the user must give the input, or “optional”, if PyPSA will use a sensible default if the user gives no input.
For functions such as Power Flow and Power System Optimization the inputs used and outputs given are listed in their documentation.
Network#
The Network
is the overall container for all components. It also
has the major functions as methods, such as network.optimize()
and
network.pf()
.
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
snapshots 
list or pandas.Index 
n/a 
[“now”] 
List of snapshots or time steps. All timedependent series quantities are indexed by 
Input (optional) 
snapshot_weightings 
pandas.DataFrame 
hours 
1 
The weightings applied to each snapshot, so that snapshots can represent more than one hour or fractions of one hour. The objective weightings are used to weight snapshots in the LOPF objective function. The store weightings determine the state of charge change for stores and storage units. The generator weightings are used when calculating global constraints. 
Input (optional) 
investment_periods 
pandas.Index 
years 
[] 
Time periods of investment. Only used for multi investment optimisation. Years have to be integer and increasing (e.g. [2025,2030,2035]). Default is an empty pd.Index([]). 
Input (optional) 
investment_period_weightings 
pandas.DataFrame 
n/a 
1 
Weightings applied to each investment period. Objective weightings are multiplied with all cost coefficients in the objective function of the respective investment period (e.g. used to include social discount rate). Years weighting denote the elapsed time until the subsequent investment period (e.g. used for global constraints CO2 emissions). 
Input (optional) 
now 
any 
n/a 
“now” 
The current snapshot/time/scenario, relevant e.g. when 
Input (optional) 
srid 
integer 
n/a 
4326 
Spatial Reference System Indentifier for x,y coordinates of buses. It defaults to standard longitude and latitude. 
Input (optional) 
crs 
CRSlike 
n/a 
n/a 
Coordinate Reference System for the Shape components. It defaults to standard longitude and latitude, given in srid. 
Input (optional) 
buses 
pandas.DataFrame 
n/a 
n/a 
All static bus information compiled by PyPSA from inputs. Index is bus names, columns are bus attributes. 
Output 
buses_t 
dictionary of pandas.DataFrames 
n/a 
n/a 
All timedependent bus information compiled by PyPSA from inputs. Dictionary keys are timedependent series attributes, index is network.snapshots, columns are bus names. 
Output 
lines 
pandas.DataFrame 
n/a 
n/a 
All static line information compiled by PyPSA from inputs. Index is line names, columns are line attributes. 
Output 
lines_t 
dictionary of pandas.DataFrames 
n/a 
n/a 
All timedependent line information compiled by PyPSA from inputs. Dictionary keys are timedependent series attributes, index is network.snapshots, columns are line names. 
Output 
components 
pandas.DataFrame 
n/a 
n/a 
For each component type (buses, lines, etc.): static component information compiled by PyPSA from inputs. Index is component names, columns are component attributes. 
Output 
components_t 
dictionary of pandas.DataFrames 
n/a 
n/a 
For each component type (buses, lines, etc.): timedependent component information compiled by PyPSA from inputs. Dictionary keys are timedependent series attributes, index is network.snapshots, columns are component names. 
Output 
branches() 
pandas.DataFrame 
n/a 
n/a 
Dynamically generated concatenation of branch DataFrames: network.lines, network.transformers and network.links. Note that this is a copy and therefore changing entries will NOT update the original. 
Output 
graph() 
networkx. OrderedMultiGraph 
n/a 
n/a 
Graph of network. 
Output 
SubNetwork#
Subnetworks are determined by PyPSA and should not be entered by the user.
Subnetworks are subsets of buses and passive branches (i.e. lines and transformers) that are connected.
They have a uniform energy carrier
inherited from the buses, such as
“DC”, “AC”, “heat” or “gas”. In the case of “AC” subnetworks, these
correspond to synchronous areas. Only “AC” and “DC” subnetworks can
contain passive branches; all other subnetworks must contain a single
isolated bus.
The power flow in subnetworks is determined by the passive flow through passive branches due to the impedances of the passive branches.
SubNetwork are determined by calling
network.determine_network_topology()
.
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name based on order of subnetwork in list of subnetworks. 
Output 
carrier 
string 
n/a 
AC 
Energy carrier: could be for example “AC” or “DC” (for electrical networks) or “gas” or “heat”. The carrier is determined from the buses in sub_network. 
Output 
slack_bus 
string 
n/a 
n/a 
Name of slack bus. 
Output 
Bus#
The bus is the fundamental node of the network, to which components like loads, generators and transmission lines attach. It enforces energy conservation for all elements feeding in and out of it (i.e. like Kirchhoff’s Current Law).
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
v_nom 
float 
kV 
1 
Nominal voltage 
Input (optional) 
type 
string 
n/a 
n/a 
Placeholder for bus type. Not yet implemented. 
Input (optional) 
x 
float 
n/a 
0 
Position (e.g. longitude); the Spatial Reference System Identifier (SRID) is set in network.srid. 
Input (optional) 
y 
float 
n/a 
0 
Position (e.g. latitude); the Spatial Reference System Identifier (SRID) is set in network.srid. 
Input (optional) 
carrier 
string 
n/a 
AC 
Energy carrier: can be “AC” or “DC” for electrical buses, or “heat” or “gas”. 
Input (optional) 
unit 
string 
n/a 
None 
Unit of the bus’ carrier if the implicitly assumed unit (“MW”) is inappropriate (e.g. “t/h”, “MWh_th/h”). Only descriptive. Does not influence any PyPSA functions. 
Input (optional) 
v_mag_pu_set 
static or series 
per unit 
1 
Voltage magnitude set point, per unit of v_nom. 
Input (optional) 
v_mag_pu_min 
float 
per unit 
0 
Minimum desired voltage, per unit of v_nom. This is a placeholder attribute and is not currently used by any PyPSA functions. 
Input (optional) 
v_mag_pu_max 
float 
per unit 
inf 
Maximum desired voltage, per unit of v_nom. This is a placeholder attribute and is not currently used by any PyPSA functions. 
Input (optional) 
control 
string 
n/a 
PQ 
P,Q,V control strategy for PF, must be “PQ”, “PV” or “Slack”. Note that this attribute is an output inherited from the controls of the generators attached to the bus; setting it directly on the bus will not have any effect. 
Output 
generator 
string 
n/a 
n/a 
Name of slack generator attached to slack bus. 
Output 
sub_network 
string 
n/a 
n/a 
Name of connected subnetwork to which bus belongs. This attribute is set by PyPSA in the function network.determine_network_topology(); do not set it directly by hand. 
Output 
p 
series 
MW 
active power at bus (positive if net generation at bus) 
Output 

q 
series 
MVar 
reactive power (positive if net generation at bus) 
Output 

v_mag_pu 
series 
per unit 
Voltage magnitude, per unit of v_nom 
Output 

v_ang 
series 
radians 
Voltage angle 
Output 

marginal_price 
series 
currency/MWh 
Locational marginal price from LOPF from power balance constraint 
Output 
Carrier#
The carrier describes energy carriers and defaults to AC
for
alternating current electricity networks. DC
can be set for direct
current electricity networks. It can also take arbitrary values for
arbitrary energy carriers, e.g. wind
, heat
, hydrogen
or
natural gas
.
Attributes relevant for global constraints can also be stored in this table, the canonical example being CO2 emissions of the carrier relevant for limits on CO2 emissions.
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
co2_emissions 
float 
tonnes/MWh 
0 
Emissions in CO2tonnesequivalent per MWh of primary energy (e.g. methane has 0.2 tonnes_CO2/MWh_thermal). 
Input (optional) 
color 
string 
n/a 
n/a 
plotting color 
Input (optional) 
nice_name 
string 
n/a 
n/a 
More precise descriptive name 
Input (optional) 
max_growth 
float 
MW 
inf 
maximum new installed capacity per investment period 
Input (optional) 
max_relative_growth 
float 
MW 
0 
maximum capacity ratio for new installed capacity per investment period (in addition to max_growth) 
Input (optional) 
Global Constraints#
Global constraints are added to OPF problems and apply to many components at once. Currently only constraints related to primary energy (i.e. before conversion with losses by generators) are supported, the canonical example being CO2 emissions for an optimisation period. Other primaryenergyrelated gas emissions also fall into this framework.
Other types of global constraints will be added in future, e.g. “final energy” (for limits on the share of renewable or nuclear electricity after conversion), “generation capacity” (for limits on total capacity expansion of given carriers) and “transmission capacity” (for limits on the total expansion of lines and links).
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
type 
string 
n/a 
primary_energy 
Type of constraint (only “primary energy”, i.e. limits on the usage of primary energy before generator conversion, is supported at the moment) 
Input (optional) 
investment_period 
float 
n/a 
NaN 
time period when the constraint is applied, if not specified, constraint is applied to all investment periods 
Input (optional) 
carrier_attribute 
string 
n/a 
co2_emissions 
If the global constraint is connected with an energy carrier, name the associated carrier attribute. This must appear as a column in network.carriers. 
Input (optional) 
sense 
string 
n/a 
== 
Constraint sense; must be one of <=, == or >= 
Input (optional) 
constant 
float 
n/a 
0 
Constant for righthandside of constraint for optimisation period. For a CO2 constraint, this would be tonnes of CO2equivalent emissions. 
Input (optional) 
mu 
float 
currency/constant 
0 
Shadow price of global constraint 
Output 
Generator#
Generators attach to a single bus and can feed in power. It converts
energy from its carrier
to the carriertype of the bus to which it
is attached.
In the linear optimal power flow (LOPF) the limits which a generator can output are set by
p_nom*p_max_pu
and p_nom*p_min_pu
, i.e. by limits defined per
unit of the nominal power p_nom
.
Generators can either have static or timevarying p_max_pu
and
p_min_pu
.
Generators with static limits are like controllable conventional
generators which can dispatch anywhere between p_nom*p_min_pu
and
p_nom*p_max_pu
at all times. The static factor p_max_pu
,
stored at network.generator.loc[gen_name,"p_max_pu"]
essentially
acts like a derating factor.
Generators with timevarying limits are like variable
weatherdependent renewable generators. The time series p_max_pu
,
stored as a series in network.generators_t.p_max_pu[gen_name]
,
dictates the active power availability for each snapshot per unit of
the nominal power p_nom
and another time series p_min_pu
which
dictates the minimum dispatch.
This time series is then multiplied by p_nom
to get the available
power dispatch, which is the maximum that may be dispatched. The
actual dispatch p
, stored in network.generators_t.p[gen_name]
,
may be below this value.
For the implementation of unit commitment, see Unit commitment constraints for generators and links.
For generators, if \(p>0\) the generator is supplying active power to the bus and if \(q>0\) it is supplying reactive power (i.e. behaving like a capacitor).
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
bus 
string 
n/a 
n/a 
name of bus to which generator is attached 
Input (required) 
control 
string 
n/a 
PQ 
P,Q,V control strategy for PF, must be “PQ”, “PV” or “Slack”. 
Input (optional) 
type 
string 
n/a 
n/a 
Placeholder for generator type. Not yet implemented. 
Input (optional) 
p_nom 
float 
MW 
0 
Nominal power for limits in optimization. 
Input (optional) 
p_nom_mod 
float 
MW 
0 
Nominal power of the generator module. 
Input (optional) 
p_nom_extendable 
boolean 
n/a 
False 
Switch to allow capacity p_nom to be extended in optimization. 
Input (optional) 
p_nom_min 
float 
MW 
0 
If p_nom is extendable in optimization, set its minimum value. 
Input (optional) 
p_nom_max 
float 
MW 
inf 
If p_nom is extendable in optimization, set its maximum value (e.g. limited by technical potential). 
Input (optional) 
p_min_pu 
static or series 
per unit 
The minimum output for each snapshot per unit of p_nom for the optimization (e.g. for variable renewable generators this can change due to weather conditions and compulsory feedin; for conventional generators it represents a minimal dispatch). Note that if comittable is False and p_min_pu > 0, this represents a mustrun condition. 
Input (optional) 

p_max_pu 
static or series 
per unit 
1 
The maximum output for each snapshot per unit of p_nom for the optimization (e.g. for variable renewable generators this can change due to weather conditions; for conventional generators it represents a maximum dispatch). 
Input (optional) 
p_set 
static or series 
MW 
active power set point (for PF) 
Input (optional) 

q_set 
static or series 
MVar 
reactive power set point (for PF) 
Input (optional) 

sign 
float 
n/a 
1 
power sign 
Input (optional) 
carrier 
string 
n/a 
n/a 
Prime mover energy carrier (e.g. coal, gas, wind, solar); required for global constraints on primary energy in optimization 
Input (optional) 
marginal_cost 
static or series 
currency/MWh 
Marginal cost of production of 1 MWh. 
Input (optional) 

marginal_cost_quadratic 
static or series 
currency/MWh 
Quadratic marginal cost of production of 1 MWh. 
Input (optional) 

build_year 
int 
year 
0 
build year 
Input (optional) 
lifetime 
float 
years 
inf 
lifetime 
Input (optional) 
capital_cost 
float 
currency/MW 
0 
Capital cost of extending p_nom by 1 MW. 
Input (optional) 
efficiency 
static or series 
per unit 
1 
Ratio between primary energy and electrical energy, e.g. takes value 0.4 MWh_elec/MWh_thermal for gas. This is required for global constraints on primary energy in optimization. 
Input (optional) 
committable 
boolean 
n/a 
False 
Use unit commitment (only possible if p_nom is not extendable). 
Input (optional) 
start_up_cost 
float 
currency 
0 
Cost to start up the generator. Only read if committable is True. 
Input (optional) 
shut_down_cost 
float 
currency 
0 
Cost to shut down the generator. Only read if committable is True. 
Input (optional) 
stand_by_cost 
static or series 
currency/h 
Standby cost for operating the generator at null power output. 
Input (optional) 

min_up_time 
int 
snapshots 
0 
Minimum number of snapshots for status to be 1. Only read if committable is True. 
Input (optional) 
min_down_time 
int 
snapshots 
0 
Minimum number of snapshots for status to be 0. Only read if committable is True. 
Input (optional) 
up_time_before 
int 
snapshots 
1 
Number of snapshots that the generator was online before network.snapshots start. Only read if committable is True and min_up_time is nonzero. 
Input (optional) 
down_time_before 
int 
snapshots 
0 
Number of snapshots that the generator was offline before network.snapshots start. Only read if committable is True and min_down_time is nonzero. 
Input (optional) 
ramp_limit_up 
static or series 
per unit 
NaN 
Maximum active power increase from one snapshot to the next, per unit of the nominal power. Ignored if NaN. 
Input (optional) 
ramp_limit_down 
static or series 
per unit 
NaN 
Maximum active power decrease from one snapshot to the next, per unit of the nominal power. Ignored if NaN. 
Input (optional) 
ramp_limit_start_up 
float 
per unit 
1 
Maximum active power increase at start up, per unit of the nominal power. Only read if committable is True. 
Input (optional) 
ramp_limit_shut_down 
float 
per unit 
1 
Maximum active power decrease at shut down, per unit of the nominal power. Only read if committable is True. 
Input (optional) 
weight 
float 
n/a 
1 
Weighting of a generator. Only used for network clustering. 
Input (optional) 
p 
series 
MW 
active power at bus (positive if net generation) 
Output 

q 
series 
MVar 
reactive power (positive if net generation) 
Output 

p_nom_opt 
float 
MW 
Optimised nominal power. 
Output 

n_mod 
int 
n/a 
0 
Optimised number of modular generators if 
Output 
status 
series 
n/a 
1 
Status (1 is on, 0 is off). Only outputted if committable is True. 
Output 
mu_upper 
series 
currency/MWh 
Shadow price of upper p_nom limit 
Output 

mu_lower 
series 
currency/MWh 
Shadow price of lower p_nom limit 
Output 

mu_p_set 
series 
currency/MWh 
Shadow price of fixed power generation p_set 
Output 

mu_ramp_limit_up 
series 
currency/MWh 
Shadow price of upper ramp up limit 
Output 

mu_ramp_limit_down 
series 
currency/MWh 
Shadow price of lower ramp down limit 
Output 
Storage Unit#
Storage units attach to a single bus and are used for intertemporal
power shifting. Each storage unit has a timevarying state of charge
and various efficiencies. The nominal energy is given as a fixed ratio
max_hours
of the nominal power. If you want to optimise the
storage energy capacity independently from the storage power capacity,
you should use a fundamental Store
component (see below) attached
with two Link
components, one for charging and one for
discharging. See also the example that replaces generators and
storage units with fundamental links and stores.
For storage units, if \(p>0\) the storage unit is supplying active power to the bus and if \(q>0\) it is supplying reactive power (i.e. behaving like a capacitor).
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
bus 
string 
n/a 
n/a 
Name of bus to which storage unit is attached. 
Input (required) 
control 
string 
n/a 
PQ 
P,Q,V control strategy for PF, must be “PQ”, “PV” or “Slack”. 
Input (optional) 
type 
string 
n/a 
n/a 
Placeholder for storage unit type. Not yet implemented. 
Input (optional) 
p_nom 
float 
MW 
0 
Nominal power for limits in OPF. 
Input (optional) 
p_nom_mod 
float 
MW 
0 
Nominal power of the storage unit module. 
Input (optional) 
p_nom_extendable 
boolean 
n/a 
False 
Switch to allow capacity p_nom to be extended in OPF. 
Input (optional) 
p_nom_min 
float 
MW 
0 
If p_nom is extendable in OPF, set its minimum value. 
Input (optional) 
p_nom_max 
float 
MW 
inf 
If p_nom is extendable in OPF, set its maximum value (e.g. limited by potential). 
Input (optional) 
p_min_pu 
static or series 
per unit 
1 
The minimum output for each snapshot per unit of p_nom for the OPF (negative sign implies storing mode withdrawing power from bus). 
Input (optional) 
p_max_pu 
static or series 
per unit 
1 
The maximum output for each snapshot per unit of p_nom for the OPF. 
Input (optional) 
p_set 
static or series 
MW 
0 
active power set point (for PF) 
Input (optional) 
q_set 
static or series 
MVar 
0 
reactive power set point (for PF) 
Input (optional) 
sign 
float 
n/a 
1 
power sign 
Input (optional) 
carrier 
string 
n/a 
n/a 
Prime mover energy carrier (e.g. coal, gas, wind, solar); required for global constraints on primary energy in OPF 
Input (optional) 
marginal_cost 
static or series 
currency/MWh 
0 
Marginal cost of production of 1 MWh. 
Input (optional) 
marginal_cost_quadratic 
static or series 
currency/MWh 
0 
Quadratic marginal cost of production (discharge) of 1 MWh. 
Input (optional) 
capital_cost 
float 
currency/MW 
0 
Capital cost of extending p_nom by 1 MW. 
Input (optional) 
build_year 
int 
year 
0 
build year 
Input (optional) 
lifetime 
float 
years 
inf 
lifetime 
Input (optional) 
state_of_charge_initial 
float 
MWh 
0 
State of charge before the snapshots in the OPF. 
Input (optional) 
state_of_charge_initial_per_period 
boolean 
n/a 
False 
Switch: if True, then state of charge at the beginning of an investment period is set to state_of_charge_initial 
Input (optional) 
state_of_charge_set 
static or series 
MWh 
NaN 
State of charge set points for snapshots in the OPF. 
Input (optional) 
cyclic_state_of_charge 
boolean 
n/a 
False 
Switch: if True, then state_of_charge_initial is ignored and the initial state of charge is set to the final state of charge for the group of snapshots in the OPF (soc[1] = soc[len(snapshots)1]). 
Input (optional) 
cyclic_state_of_charge_per_period 
boolean 
n/a 
True 
Switch: if True, then the cyclic constraints are applied to each period (first snapshot level if multiindexed) separately. 
Input (optional) 
max_hours 
float 
hours 
1 
Maximum state of charge capacity in terms of hours at full output capacity p_nom 
Input (optional) 
efficiency_store 
static or series 
per unit 
1 
Efficiency of storage on the way into the storage. 
Input (optional) 
efficiency_dispatch 
static or series 
per unit 
1 
Efficiency of storage on the way out of the storage. 
Input (optional) 
standing_loss 
static or series 
per unit 
0 
Losses per hour to state of charge. 
Input (optional) 
inflow 
static or series 
MW 
0 
Inflow to the state of charge, e.g. due to river inflow in hydro reservoir. 
Input (optional) 
p 
series 
MW 
0 
active power at bus (positive if net generation) 
Output 
p_dispatch 
series 
MW 
0 
active power dispatch at bus 
Output 
p_store 
series 
MW 
0 
active power charging at bus 
Output 
q 
series 
MVar 
0 
reactive power (positive if net generation) 
Output 
state_of_charge 
series 
MWh 
NaN 
State of charge as calculated by the OPF. 
Output 
spill 
series 
MW 
0 
Spillage for each snapshot. 
Output 
p_nom_opt 
float 
MW 
0 
Optimised nominal power. 
Output 
n_mod 
int 
n/a 
0 
Optimised number of moudaler storage units if 
Output 
mu_upper 
series 
currency/MWh 
0 
Shadow price of upper p_nom limit 
Output 
mu_lower 
series 
currency/MWh 
0 
Shadow price of lower p_nom limit 
Output 
mu_state_of_charge_set 
series 
currency/MWh 
0 
Shadow price of fixed state of charge state_of_charge_set 
Output 
mu_energy_balance 
series 
currency/MWh 
0 
Shadow price of storage consistency equations 
Output 
Store#
The Store
connects to a single bus. It is a more fundamental
component for storing energy only (it cannot convert between energy
carriers). It inherits its energy carrier from the bus to which it is
attached.
The Store, Bus and Link are fundamental components with which one can build more complicated components (Generators, Storage Units, CHPs, etc.).
The Store has controls and optimisation on the size of its energy capacity, but not it’s power output; to control the power output, you must put a link in front of it, see the example that replaces generators and storage units with fundamental links and stores.
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
bus 
string 
n/a 
n/a 
Name of bus to which store is attached. 
Input (required) 
type 
string 
n/a 
n/a 
Placeholder for store type. Not yet implemented. 
Input (optional) 
carrier 
string 
n/a 
Energy carrier of the Store, e.g. “heat” or “gas”. 
Input (optional) 

e_nom 
float 
MWh 
0 
Nominal energy capacity. 
Input (optional) 
e_nom_mod 
float 
MWh 
0 
Nominal energy capacity of the store module. 
Input (optional) 
e_nom_extendable 
boolean 
n/a 
False 
Switch to allow capacity e_nom to be extended in OPF. 
Input (optional) 
e_nom_min 
float 
MWh 
0 
If e_nom is extendable in OPF, set its minimum value. 
Input (optional) 
e_nom_max 
float 
MWh 
inf 
If e_nom is extendable in OPF, set its maximum value (e.g. limited by technical potential). 
Input (optional) 
e_min_pu 
static or series 
per unit 
0 
Minimal value of e relative to e_nom for the OPF. 
Input (optional) 
e_max_pu 
static or series 
per unit 
1 
Maximal value of e relative to e_nom for the OPF. 
Input (optional) 
e_initial 
float 
MWh 
0 
Energy before the snapshots in the OPF. 
Input (optional) 
e_initial_per_period 
boolean 
n/a 
False 
Switch: if True, then at the beginning of each investment period e is set to e_initial 
Input (optional) 
e_cyclic 
boolean 
n/a 
False 
Switch: if True, then e_initial is ignored and the initial energy is set to the final energy for the group of snapshots in the OPF. 
Input (optional) 
e_cyclic_per_period 
boolean 
n/a 
True 
Switch: if True, then the cyclic constraints are applied to each period (first snapshot level if multiindexed) separately. 
Input (optional) 
p_set 
static or series 
MW 
0 
active power set point (for PF) 
Input (optional) 
q_set 
static or series 
MVar 
0 
reactive power set point (for PF) 
Input (optional) 
sign 
float 
n/a 
1 
power sign 
Input (optional) 
marginal_cost 
static or series 
currency/MWh 
0 
Marginal cost of production of 1 MWh. 
Input (optional) 
marginal_cost_quadratic 
static or series 
currency/MWh 
0 
Quadratic marginal cost of production (discharge) of 1 MWh. 
Input (optional) 
capital_cost 
float 
currency/MWh 
0 
Capital cost of extending e_nom by 1 MWh. 
Input (optional) 
standing_loss 
static or series 
per unit 
0 
Losses per hour to energy. 
Input (optional) 
build_year 
int 
year 
0 
build year 
Input (optional) 
lifetime 
float 
years 
inf 
lifetime 
Input (optional) 
p 
series 
MW 
0 
active power at bus (positive if net generation) 
Output 
q 
series 
MVar 
0 
reactive power (positive if net generation) 
Output 
e 
series 
MWh 
0 
Energy as calculated by the OPF. 
Output 
e_nom_opt 
float 
MWh 
0 
Optimised nominal energy capacity outputed by OPF. 
Output 
n_mod 
int 
n/a 
0 
Optimised number of modular stores if 
Output 
mu_upper 
series 
currency/MWh 
0 
Shadow price of upper e_nom limit 
Output 
mu_lower 
series 
currency/MWh 
0 
Shadow price of lower e_nom limit 
Output 
mu_energy_balance 
series 
currency/MWh 
0 
Shadow price of storage consistency equations 
Output 
Load#
The load attaches to a single bus and consumes power as a PQ load.
For loads, if \(p>0\) the load is consuming active power from the bus and if \(q>0\) it is consuming reactive power (i.e. behaving like an inductor).
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
bus 
string 
n/a 
n/a 
Name of bus to which load is attached. 
Input (required) 
carrier 
string 
n/a 
n/a 
Energy carrier: can be “AC” or “DC” for electrical buses, or “heat” or “gas”. 
Input (optional) 
type 
string 
n/a 
n/a 
Placeholder for load type. Not yet implemented. 
Input (optional) 
p_set 
static or series 
MW 
0 
Active power consumption (positive if the load is consuming power). 
Input (optional) 
q_set 
static or series 
MVar 
0 
Reactive power consumption (positive if the load is inductive). 
Input (optional) 
sign 
float 
n/a 
1 
power sign (opposite sign to generator) 
Input (optional) 
p 
series 
MW 
0 
active power at bus (positive if net load) 
Output 
q 
series 
MVar 
0 
reactive power (positive if net load) 
Output 
Shunt Impedance#
Shunt impedances attach to a single bus and have a voltagedependent admittance.
For shunt impedances the power consumption is given by \(s_i = V_i^2 y_i^*\) so that \(p_i + j q_i = V_i^2 (g_i jb_i)\). However the p and q below are defined directly proportional to g and b \(p = V^2g\) and \(q = V^2b\), thus if \(p>0\) the shunt impedance is consuming active power from the bus and if \(q>0\) it is supplying reactive power (i.e. behaving like an capacitor).
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
bus 
string 
n/a 
n/a 
name of bus to which generator is attached 
Input (required) 
g 
float 
Siemens 
Shunt conductivity. 
Input (optional) 

b 
float 
Siemens 
Shunt susceptance. 
Input (optional) 

sign 
float 
n/a 
1. 
power sign (sign convention so that g>0 withdraws p from bus) 
Input (optional) 
p 
series 
MW 
active power at bus (positive if net load) 
Output 

q 
series 
MVar 
reactive power (positive if net generation) 
Output 

g_pu 
float 
per unit 
Calculated from g and bus.v_nom. 
Output 

b_pu 
float 
per unit 
Calculated from b and bus.v_nom. 
Output 
Line#
Lines represent transmission and distribution lines. They connect a
bus0
to a bus1
. They can connect either AC buses or DC
buses. Power flow through lines is not directly controllable, but is
determined passively by their impedances and the nodal power
imbalances. To see how the impedances are used in the power flow, see
Line model.
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
bus0 
string 
n/a 
n/a 
Name of first bus to which branch is attached. 
Input (required) 
bus1 
string 
n/a 
n/a 
Name of second bus to which branch is attached. 
Input (required) 
type 
string 
n/a 
n/a 
Name of line standard type. If this is not an empty string “”, then the line standard type impedance parameters are multiplied with the line length and divided/multiplied by num_parallel to compute x, r, etc. This will override any values set in r, x, and b. If the string is empty, PyPSA will simply read r, x, etc. 
Input (optional) 
x 
float 
Ohm 
0 
Series reactance, must be nonzero for AC branch in linear power flow. If the line has series inductance \(L\) in Henries then \(x = 2\pi f L\) where \(f\) is the frequency in Hertz. Series impedance \(z = r + jx\) must be nonzero for the nonlinear power flow. Ignored if type defined. 
Input (required) 
r 
float 
Ohm 
0 
Series resistance, must be nonzero for DC branch in linear power flow. Series impedance \(z = r + jx\) must be nonzero for the nonlinear power flow. Ignored if type defined. 
Input (required) 
g 
float 
Siemens 
0 
Shunt conductivity. Shunt admittance is \(y = g + jb\). 
Input (optional) 
b 
float 
Siemens 
0 
Shunt susceptance. If the line has shunt capacitance \(C\) in Farads then \(b = 2\pi f C\) where \(f\) is the frequency in Hertz. Shunt admittance is \(y = g + jb\). Ignored if type defined. 
Input (optional) 
s_nom 
float 
MVA 
0 
Limit of apparent power which can pass through branch. 
Input (optional) 
s_nom_mod 
float 
MWA 
0 
Limit of apparent power of the line module. 
Input (optional) 
s_nom_extendable 
boolean 
n/a 
False 
Switch to allow capacity s_nom to be extended in OPF. 
Input (optional) 
s_nom_min 
float 
MVA 
0 
If s_nom is extendable in OPF, set its minimum value. 
Input (optional) 
s_nom_max 
float 
MVA 
inf 
If s_nom is extendable in OPF, set its maximum value (e.g. limited by potential). 
Input (optional) 
s_max_pu 
static or series 
per unit 
1 
The maximum allowed absolute flow per unit of s_nom for the OPF (e.g. can be set <1 to approximate n1 factor, or can be timevarying to represent weatherdependent dynamic line rating for overhead lines). 
Input (optional) 
capital_cost 
float 
currency/MVA 
0 
Capital cost of extending s_nom by 1 MVA. 
Input (optional) 
build_year 
int 
year 
0 
build year 
Input (optional) 
lifetime 
float 
years 
inf 
lifetime 
Input (optional) 
length 
float 
km 
0 
Length of line used when “type” is set, also useful for calculating the capital cost. 
Input (optional) 
carrier 
string 
n/a 
Type of current, “AC” is the only valid value 
Input (optional) 

terrain_factor 
float 
per unit 
1 
Terrain factor for increasing capital cost. 
Input (optional) 
num_parallel 
float 
n/a 
1 
When “type” is set, this is the number of parallel lines (can also be fractional). If “type” is empty “” this value is ignored. 
Input (optional) 
v_ang_min 
float 
Degrees 
inf 
Minimum voltage angle difference across the line. This is a placeholder attribute and is not currently used by any PyPSA functions. 
Input (optional) 
v_ang_max 
float 
Degrees 
inf 
Maximum voltage angle difference across the line. This is a placeholder attribute and is not currently used by any PyPSA functions. 
Input (optional) 
sub_network 
string 
n/a 
n/a 
Name of connected subnetwork to which lines belongs. This attribute is set by PyPSA in the function network.determine_network_topology(); do not set it directly by hand. 
Output 
p0 
series 
MW 
Active power at bus0 (positive if branch is withdrawing power from bus0). 
Output 

q0 
series 
MVar 
Reactive power at bus0 (positive if branch is withdrawing power from bus0). 
Output 

p1 
series 
MW 
Active power at bus1 (positive if branch is withdrawing power from bus1). 
Output 

q1 
series 
MVar 
Reactive power at bus1 (positive if branch is withdrawing power from bus1). 
Output 

x_pu 
float 
per unit 
0 
Per unit series reactance calculated by PyPSA from x and bus.v_nom. 
Output 
r_pu 
float 
per unit 
0 
Per unit series resistance calculated by PyPSA from r and bus.v_nom 
Output 
g_pu 
float 
per unit 
0 
Per unit shunt conductivity calculated by PyPSA from g and bus.v_nom 
Output 
b_pu 
float 
per unit 
0 
Per unit shunt susceptance calculated by PyPSA from b and bus.v_nom 
Output 
x_pu_eff 
float 
per unit 
0 
Effective per unit series reactance for linear power flow, calculated by PyPSA from x, tap_ratio for transformers and bus.v_nom. 
Output 
r_pu_eff 
float 
per unit 
0 
Effective per unit series resistance for linear power flow, calculated by PyPSA from x, tap_ratio for transformers and bus.v_nom. 
Output 
s_nom_opt 
float 
MVA 
0 
Optimised capacity for apparent power. 
Output 
n_mod 
int 
n/a 
0 
Optimised number of modular lines if 
Output 
mu_lower 
series 
currency/MVA 
Shadow price of lower s_nom limit F leq f. Always nonnegative. 
Output 

mu_upper 
series 
currency/MVA 
Shadow price of upper s_nom limit f leq F. Always nonnegative. 
Output 
Line Types#
Standard line types with per length values for impedances.
If for a line the attribute “type” is nonempty, then these values are multiplied with the line length to get the line’s electrical parameters.
The line type parameters in the following table and the implementation in PyPSA are based on pandapower’s standard types, whose parameterisation is in turn loosely based on DIgSILENT PowerFactory.
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
f_nom 
float 
Hz 
Nominal frequency 
Input (required) 

r_per_length 
float 
Ohm per km 
Series resistance per length 
Input (required) 

x_per_length 
float 
Ohm per km 
Series resistance per length 
Input (required) 

c_per_length 
float 
nF per km 
Shunt capacitance per length 
Input (optional) 

i_nom 
float 
kA 
Nominal current 
Input (optional) 

mounting 
string 
n/a 
ol 
Can be “ol” for overhead line or “cs” for cable 
Input (optional) 
cross_section 
float 
mm2 
Wire crosssection 
Input (optional) 

references 
string 
n/a 
n/a 
References for electrical parameters 
Input (optional) 
If you do not import your own line types, then PyPSA will provide standard types using the following table. We thank the pandapower team for allowing us to include this data. We take no responsibility for the accuracy of the values.
name 
f_nom 
r_per_length 
x_per_length 
c_per_length 
i_nom 
mounting 
cross_section 
references 

149AL1/24ST1A 10.0 
0.194 
0.315 
11.25 
0.47 
ol 
149 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

149AL1/24ST1A 110.0 
0.194 
0.41 
8.75 
0.47 
ol 
149 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

149AL1/24ST1A 20.0 
0.194 
0.337 
10.5 
0.47 
ol 
149 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

15AL1/3ST1A 0.4 
1.8769 
0.35 
11 
0.105 
ol 
16 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

184AL1/30ST1A 110.0 
0.1571 
0.4 
8.8 
0.535 
ol 
184 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

184AL1/30ST1A 20.0 
0.1571 
0.33 
10.75 
0.535 
ol 
184 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

24AL1/4ST1A 0.4 
1.2012 
0.335 
11.25 
0.14 
ol 
24 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

243AL1/39ST1A 110.0 
0.1188 
0.39 
9 
0.645 
ol 
243 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

243AL1/39ST1A 20.0 
0.1188 
0.32 
11 
0.645 
ol 
243 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

305AL1/39ST1A 110.0 
0.0949 
0.38 
9.2 
0.74 
ol 
305 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

48AL1/8ST1A 0.4 
0.5939 
0.3 
12.2 
0.21 
ol 
48 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

48AL1/8ST1A 10.0 
0.5939 
0.35 
10.1 
0.21 
ol 
48 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

48AL1/8ST1A 20.0 
0.5939 
0.372 
9.5 
0.21 
ol 
48 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

490AL1/64ST1A 220.0 
0.059 
0.285 
10 
0.96 
ol 
490 
pandapower 

490AL1/64ST1A 380.0 
0.059 
0.253 
11 
0.96 
ol 
490 
pandapower 

94AL1/15ST1A 0.4 
0.306 
0.29 
13.2 
0.35 
ol 
94 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

94AL1/15ST1A 10.0 
0.306 
0.33 
10.75 
0.35 
ol 
94 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

94AL1/15ST1A 20.0 
0.306 
0.35 
10 
0.35 
ol 
94 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013) 

N2XS(FL)2Y 1x120 RM/35 64/110 kV 
0.153 
0.166 
112 
0.366 
cs 
120 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013);Werth Netzberechnung mit Erzeugungsprofilen 

N2XS(FL)2Y 1x185 RM/35 64/110 kV 
0.099 
0.156 
125 
0.457 
cs 
185 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013);Werth Netzberechnung mit Erzeugungsprofilen 

N2XS(FL)2Y 1x240 RM/35 64/110 kV 
0.075 
0.149 
135 
0.526 
cs 
240 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013);Werth Netzberechnung mit Erzeugungsprofilen 

N2XS(FL)2Y 1x300 RM/35 64/110 kV 
0.06 
0.144 
144 
0.588 
cs 
300 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013);Werth Netzberechnung mit Erzeugungsprofilen 

NA2XS2Y 1x185 RM/25 12/20 kV 
0.161 
0.117 
273 
0.362 
cs 
185 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013);Werth Netzberechnung mit Erzeugungsprofilen 

NA2XS2Y 1x240 RM/25 12/20 kV 
0.122 
0.112 
304 
0.421 
cs 
240 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013);Werth Netzberechnung mit Erzeugungsprofilen 

NA2XS2Y 1x95 RM/25 12/20 kV 
0.313 
0.132 
216 
0.252 
cs 
95 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013);Werth Netzberechnung mit Erzeugungsprofilen 

NAYY 4x120 SE 
0.225 
0.08 
264 
0.242 
cs 
120 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013);Werth Netzberechnung mit Erzeugungsprofilen 

NAYY 4x150 SE 
0.208 
0.08 
261 
0.27 
cs 
150 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013);Werth Netzberechnung mit Erzeugungsprofilen 

NAYY 4x50 SE 
0.642 
0.083 
210 
0.142 
cs 
50 
pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013);Werth Netzberechnung mit Erzeugungsprofilen 

Al/St 240/40 2bundle 220.0 
0.06 
0.301 
12.5 
1.29 
ol 
240 
Oeding and Oswald “Elektrische Kraftwerke und Netze”, 2011, Chapter 9 

Al/St 240/40 3bundle 300.0 
0.04 
0.265 
13.2 
1.935 
ol 
240 
Oeding and Oswald “Elektrische Kraftwerke und Netze”, 2011, Chapter 9 

Al/St 240/40 4bundle 380.0 
0.03 
0.246 
13.8 
2.58 
ol 
240 
Oeding and Oswald “Elektrische Kraftwerke und Netze”, 2011, Chapter 9 

Al/St 560/50 4bundle 750.0 
0.013 
0.276 
13.13 
4.16 
ol 
560 
Oeding and Oswald “Elektrische Kraftwerke und Netze”, 2011, Appendix 

HVDC XLPE 1000 
0.0022 
0.000001 
10000 
1.638 
2500 
Regional Group North Sea, “Offshore Transmission Technology,”ENTSOE AISBL, Brussels, Belgium, Tech. Rep., 2011. P.2122 

HVDC Oil filled 1400 
0.00264 
0.000001 
10000 
2.8 
3000 
Regional Group North Sea, “Offshore Transmission Technology,”ENTSOE AISBL, Brussels, Belgium, Tech. Rep., 2011. P.1920 
Transformer#
Transformers represent 2winding transformers that convert AC power
from one voltage level to another. They connect a bus0
(typically at higher voltage) to a
bus1
(typically at lower voltage). Power flow through transformers is not
directly controllable, but is determined passively by their impedances
and the nodal power imbalances. To see how the impedances are used in
the power flow, see Transformer model.
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
bus0 
string 
n/a 
n/a 
Name of first bus (typically higher voltage) to which transformer is attached. 
Input (required) 
bus1 
string 
n/a 
n/a 
Name of second bus (typically lower voltage) to which transformer is attached. 
Input (required) 
type 
string 
n/a 
n/a 
Name of 2winding transformer standard type. If this is not an empty string “”, then the transformer type impedance parameters are taken from the standard type along with “num_parallel”. This will override any values set in r, x, g, b, s_nom, tap_ratio, tap_side and phase_shift. If the string is empty, PyPSA will simply read r, x, etc. 
Input (optional) 
model 
string 
n/a 
t 
Model used for admittance matrix; can be “t” or “pi”; since PyPSA Version 0.8.0 it defaults to “t” following physics and DIgSILENT PowerFactory; versions of PyPSA before 0.8.0 and some other power system tools, like MATPOWER, PYPOWER, PSS/SINCAL use the less physical “pi” model. 
Input (required) 
x 
float 
per unit 
0 
Series reactance (per unit, using s_nom as base power); must be nonzero for AC branch in linear power flow. Series impedance \(z = r + jx\) must be nonzero for the nonlinear power flow. Ignored if type defined. 
Input (required) 
r 
float 
per unit 
0 
Series resistance (per unit, using s_nom as base power); must be nonzero for DC branch in linear power flow. Series impedance \(z = r + jx\) must be nonzero for the nonlinear power flow. Ignored if type defined. 
Input (required) 
g 
float 
per unit 
0 
Shunt conductivity (per unit, using s_nom as base power). Ignored if type defined. 
Input (optional) 
b 
float 
per unit 
0 
Shunt susceptance (per unit, using s_nom as base power). Ignored if type defined. 
Input (optional) 
s_nom 
float 
MVA 
0 
Limit of apparent power which can pass through branch. 
Input (optional) 
s_nom_mod 
float 
MWA 
0 
Limit of apparent power of the transformer module. 
Input (optional) 
s_nom_extendable 
boolean 
n/a 
False 
Switch to allow capacity s_nom to be extended in OPF. 
Input (optional) 
s_nom_min 
float 
MVA 
0 
If s_nom is extendable in OPF, set its minimum value. 
Input (optional) 
s_nom_max 
float 
MVA 
inf 
If s_nom is extendable in OPF, set its maximum value (e.g. limited by potential). 
Input (optional) 
s_max_pu 
static or series 
per unit 
1 
The maximum allowed absolute flow per unit of s_nom for the OPF. 
Input (optional) 
capital_cost 
float 
currency/MVA 
0 
Capital cost of extending s_nom by 1 MVA. 
Input (optional) 
num_parallel 
float 
n/a 
1 
When “type” is set, this is the number of parallel transformers (can also be fractional). If “type” is empty “” this value is ignored. 
Input (optional) 
tap_ratio 
float 
per unit 
1 
Ratio of per unit voltages at each bus for tap changed. Ignored if type defined. 
Input (optional) 
tap_side 
int 
n/a 
0 
Defines if tap changer is modelled at the primary 0 side (usually highvoltage) or the secondary 1 side (usually low voltage) (must be 0 or 1, defaults to 0). Ignored if type defined. 
Input (optional) 
tap_position 
int 
n/a 
0 
If the transformer has a type, determines position relative to the neutral tap position. 
Input (optional) 
phase_shift 
float 
Degrees 
0 
Voltage phase angle shift. Ignored if type defined. 
Input (optional) 
build_year 
int 
year 
0 
build year 
Input (optional) 
lifetime 
float 
years 
inf 
lifetime 
Input (optional) 
v_ang_min 
float 
Degrees 
inf 
Minimum voltage angle difference across the transformer. This is a placeholder attribute and is not currently used by any PyPSA functions. 
Input (optional) 
v_ang_max 
float 
Degrees 
inf 
Maximum voltage angle difference across the transformer. This is a placeholder attribute and is not currently used by any PyPSA functions. 
Input (optional) 
sub_network 
string 
n/a 
n/a 
Name of connected subnetwork to which transformer belongs. This attribute is set by PyPSA in the function network.determine_network_topology(); do not set it directly by hand. 
Output 
p0 
series 
MW 
0 
Active power at bus0 (positive if branch is withdrawing power from bus0). 
Output 
q0 
series 
MVar 
0 
Reactive power at bus0 (positive if branch is withdrawing power from bus0). 
Output 
p1 
series 
MW 
0 
Active power at bus1 (positive if branch is withdrawing power from bus1). 
Output 
q1 
series 
MVar 
0 
Reactive power at bus1 (positive if branch is withdrawing power from bus1). 
Output 
x_pu 
float 
per unit 
0 
Per unit series reactance calculated by PyPSA from x and bus.v_nom. 
Output 
r_pu 
float 
per unit 
0 
Per unit series resistance calculated by PyPSA from r and bus.v_nom 
Output 
g_pu 
float 
per unit 
0 
Per unit shunt conductivity calculated by PyPSA from g and bus.v_nom 
Output 
b_pu 
float 
per unit 
0 
Per unit shunt susceptance calculated by PyPSA from b and bus.v_nom 
Output 
x_pu_eff 
float 
per unit 
0 
Effective per unit series reactance for linear power flow, calculated by PyPSA from x, tap_ratio for transformers and bus.v_nom. 
Output 
r_pu_eff 
float 
per unit 
0 
Effective per unit series resistance for linear power flow, calculated by PyPSA from x, tap_ratio for transformers and bus.v_nom. 
Output 
s_nom_opt 
float 
MVA 
0 
Optimised capacity for apparent power. 
Output 
n_mod 
int 
n/a 
0 
Optimised number of modular transformers if 
Output 
mu_lower 
series 
currency/MVA 
0 
Shadow price of lower s_nom limit F leq f. Always nonnegative. 
Output 
mu_upper 
series 
currency/MVA 
0 
Shadow price of upper s_nom limit f leq F. Always nonnegative. 
Output 
Transformer Types#
Standard 2winding transformer types.
If for a transformer the attribute “type” is nonempty, then these values are used for the transformer’s electrical parameters.
The transformer type parameters in the following table and the implementation in PyPSA are based on pandapower’s standard types, whose parameterisation is in turn loosely based on DIgSILENT PowerFactory.
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
f_nom 
float 
Hz 
Nominal frequency 
Input (required) 

s_nom 
float 
MVA 
Rated apparent power 
Input (required) 

v_nom_0 
float 
kV 
Nominal voltage on high voltage side 
Input (required) 

v_nom_1 
float 
kV 
Nominal voltage on low voltage side 
Input (required) 

vsc 
float 
Percent 
Short circuit voltage 
Input (required) 

vscr 
float 
Percent 
Real part of short circuit voltage 
Input (required) 

pfe 
float 
kW 
No load (open circuit) iron losses 
Input (required) 

i0 
float 
Percent 
No load (open circuit) current 
Input (required) 

phase_shift 
float 
Degrees 
Phase shift angle 
Input (required) 

tap_side 
int 
n/a 
0 
Defines if tap changer is modelled at the primary 0 side (usually highvoltage) or the secondary 1 side (usually low voltage) (must be 0 or 1, defaults to 0) 
Input (required) 
tap_neutral 
int 
n/a 
0 
rated tap position, i.e. position at which the winding ratio corresponds to the ratio of the rated voltages 
Input (required) 
tap_min 
int 
n/a 
0 
minimum tap position 
Input (required) 
tap_max 
int 
n/a 
0 
maximum tap position 
Input (required) 
tap_step 
float 
Percent 
tap step size in percentage of voltage change 
Input (required) 

references 
string 
n/a 
n/a 
References for electrical parameters 
Input (optional) 
If you do not import your own transformer types, then PyPSA will provide standard types using the following table. This table was initially based on pandapower’s standard types and we thank the pandapower team for allowing us to include this data. We take no responsibility for the accuracy of the values.
name 
f_nom 
s_nom 
v_nom_0 
v_nom_1 
vsc 
vscr 
pfe 
i0 
phase_shift 
tap_side 
tap_neutral 
tap_min 
tap_max 
tap_step 
references 

0.25 MVA 10/0.4 kV 
0.250 
10 
0.4 
4 
1.2 
0.6 
0.24 
150 
0 
0 
2 
2 
2.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

0.25 MVA 20/0.4 kV 
0.250 
20 
0.4 
6 
1.44 
0.8 
0.32 
150 
0 
0 
2 
2 
2.5 
pandapowe;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilenr 

0.4 MVA 10/0.4 kV 
0.400 
10 
0.4 
4 
1.325 
0.95 
0.2375 
150 
0 
0 
2 
2 
2.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

0.4 MVA 20/0.4 kV 
0.400 
20 
0.4 
6 
1.425 
1.35 
0.3375 
150 
0 
0 
2 
2 
2.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

0.63 MVA 10/0.4 kV 
0.630 
10 
0.4 
4 
1.0794 
1.18 
0.1873 
150 
0 
0 
2 
2 
2.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

0.63 MVA 20/0.4 kV 
0.630 
20 
0.4 
6 
1.206 
1.65 
0.2619 
150 
0 
0 
2 
2 
2.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

100 MVA 220/110 kV 
100.0 
220.0 
110.0 
12.0 
0.26 
55 
0.06 
0 
0 
0 
9 
9 
1.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

160 MVA 380/110 kV 
160.0 
380.0 
110.0 
12.2 
0.25 
60 
0.06 
0 
0 
0 
9 
9 
1.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

25 MVA 110/10 kV 
110 
10 
10.04 
0.276 
28.51 
0.073 
150 
0 
0 
9 
9 
1.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

25 MVA 110/20 kV 
110.0 
20.0 
11.2 
0.282 
29 
0.071 
150 
0 
0 
9 
9 
1.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

40 MVA 110/10 kV 
110 
10 
10.04 
0.295 
30.45 
0.076 
150 
0 
0 
9 
9 
1.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

40 MVA 110/20 kV 
110.0 
20.0 
11.2 
0.302 
31 
0.08 
150 
0 
0 
9 
9 
1.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

63 MVA 110/10 kV 
110 
10 
10.04 
0.31 
31.51 
0.078 
150 
0 
0 
9 
9 
1.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 

63 MVA 110/20 kV 
110.0 
20.0 
11.2 
0.322 
33 
0.086 
150 
0 
0 
9 
9 
1.5 
pandapower;Oswald  Transformatoren  Vorlesungsskript Elektrische Energieversorgung I;Werth Netzberechnung mit Erzeugungsprofilen 
Link#
The Link
is a component for controllable
directed flows between two buses bus0
and bus1
with arbitrary
energy carriers. It can have an efficiency loss and a marginal cost;
for this reason its default settings allow only for power flow in one
direction, from bus0
to bus1
(i.e. p_min_pu = 0
). To build
a bidirectional lossless link, set efficiency = 1
, marginal_cost
= 0
and p_min_pu = 1
.
The Link
component can be used for any element with a controllable
power flow: a bidirectional pointtopoint HVDC link, a unidirectional
lossy HVDC link, a converter between an AC and a DC network, a heat
pump or resistive heater from an AC/DC bus to a heat bus, etc.
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
bus0 
string 
n/a 
n/a 
Name of first bus to which link is attached. 
Input (required) 
bus1 
string 
n/a 
n/a 
Name of other bus to which link is attached. 
Input (required) 
type 
string 
n/a 
n/a 
Placeholder for link type. Not yet implemented. 
Input (optional) 
carrier 
string 
n/a 
Energy carrier transported by the link: can be “DC” for electrical HVDC links, or “heat” or “gas” etc. 
Input (optional) 

efficiency 
static or series 
per unit 
1 
Efficiency of power transfer from bus0 to bus1. (Can be timedependent to represent temperaturedependent Coefficient of Performance of a heat pump from an electric to a heat bus.) 
Input (optional) 
build_year 
int 
year 
0 
build year 
Input (optional) 
lifetime 
float 
years 
inf 
lifetime 
Input (optional) 
p_nom 
float 
MW 
0 
Limit of active power which can pass through link. 
Input (optional) 
p_nom_mod 
float 
MW 
0 
Limit of active power of the link module. 
Input (optional) 
p_nom_extendable 
boolean 
n/a 
False 
Switch to allow capacity p_nom to be extended. 
Input (optional) 
p_nom_min 
float 
MW 
0 
If p_nom is extendable, set its minimum value. 
Input (optional) 
p_nom_max 
float 
MW 
inf 
If p_nom is extendable, set its maximum value (e.g. limited by potential). 
Input (optional) 
p_set 
static or series 
MW 
0 
The dispatch set point for p0 of the link in PF. 
Input (optional) 
p_min_pu 
static or series 
per unit of p_nom 
Minimal dispatch (can also be negative) per unit of p_nom for the link. 
Input (optional) 

p_max_pu 
static or series 
per unit of p_nom 
Maximal dispatch (can also be negative) per unit of p_nom for the link. 
Input (optional) 

capital_cost 
float 
currency/MW 
0 
Capital cost of extending p_nom by 1 MW. 
Input (optional) 
marginal_cost 
static or series 
currency/MWh 
Marginal cost of transfering 1 MWh (before efficiency losses) from bus0 to bus1. NB: marginal cost only makes sense if p_max_pu >= 0. 
Input (optional) 

marginal_cost_quadratic 
static or series 
currency/MWh 
Quadratic marginal cost for transferring 1 MWh (before efficiency losses) from bus0 to bus1. 
Input (optional) 

stand_by_cost 
static or series 
currency/h 
Standby cost for operating the link at null power flow. 
Input (optional) 

length 
float 
km 
0 
Length of line, useful for calculating the capital cost. 
Input (optional) 
terrain_factor 
float 
per unit 
1 
Terrain factor for increasing capital cost. 
Input (optional) 
committable 
boolean 
n/a 
False 
Use unit commitment (only possible if p_nom is not extendable). 
Input (optional) 
start_up_cost 
float 
currency 
0 
Cost to start up the link. Only read if committable is True. 
Input (optional) 
shut_down_cost 
float 
currency 
0 
Cost to shut down the link. Only read if committable is True. 
Input (optional) 
min_up_time 
int 
snapshots 
0 
Minimum number of snapshots for status to be 1. Only read if committable is True. 
Input (optional) 
min_down_time 
int 
snapshots 
0 
Minimum number of snapshots for status to be 0. Only read if committable is True. 
Input (optional) 
up_time_before 
int 
snapshots 
1 
Number of snapshots that the link was online before network.snapshots start. Only read if committable is True and min_up_time is nonzero. 
Input (optional) 
down_time_before 
int 
snapshots 
0 
Number of snapshots that the link was offline before network.snapshots start. Only read if committable is True and min_down_time is nonzero. 
Input (optional) 
ramp_limit_up 
static or series 
per unit 
NaN 
Maximum increase from one snapshot to the next, per unit of the bus0 unit. Ignored if NaN. 
Input (optional) 
ramp_limit_down 
static or series 
per unit 
NaN 
Maximum decrease from one snapshot to the next, per unit of the bus0 unit. Ignored if NaN. 
Input (optional) 
ramp_limit_start_up 
float 
per unit 
1 
Maximumincrease at start up, per unit of bus0 unit. Only read if committable is True. 
Input (optional) 
ramp_limit_shut_down 
float 
per unit 
1 
Maximum decrease at shut down, per unit of bus0 unit. Only read if committable is True. 
Input (optional) 
p0 
series 
MW 
Active power at bus0 (positive if branch is withdrawing power from bus0). 
Output 

p1 
series 
MW 
Active power at bus1 (positive if branch is withdrawing power from bus1). 
Output 

p_nom_opt 
float 
MW 
0 
Optimised capacity for active power. 
Output 
n_mod 
int 
n/a 
0 
Optimised number of modular links if 
Output 
status 
series 
n/a 
Status (1 is on, 0 is off). Only outputted if committable is True. 
Output 

mu_lower 
series 
currency/MW 
Shadow price of lower p_nom limit F leq f. Always nonnegative. 
Output 

mu_upper 
series 
currency/MW 
Shadow price of upper p_nom limit f leq F. Always nonnegative. 
Output 

mu_p_set 
series 
currency/MWh 
Shadow price of fixed power transmission p_set 
Output 

mu_ramp_limit_up 
series 
currency/MWh 
Shadow price of upper ramp up limit 
Output 

mu_ramp_limit_down 
series 
currency/MWh 
Shadow price of lower ramp down limit 
Output 
Link with multiple outputs or inputs#
Links can also be defined with multiple outputs in fixed ratio to the
power in the single input by defining new columns bus2
, bus3
,
etc. (bus
followed by an integer) in network.links
along with
associated columns for the efficiencies efficiency2
,
efficiency3
, etc. The different outputs are then equal to
the input multiplied by the corresponding efficiency; see Controllable branch flows: links for how
these are used in the LOPF and the example of a CHP with a fixed
powerheat ratio.
The columns bus2
, efficiency2
, bus3
, efficiency3
, etc. in
network.links
are automatically added to the component attributes. The
values in these columns are not compulsory; if the link has no 2nd output,
simply leave it empty network.links.at["my_link","bus2"] = ""
or as NaN.
For links with multiple inputs in fixed ratio to one of the inputs, you can define the other inputs as outputs with a negative efficiency so that they withdraw energy or material from the bus if there is a positive flow in the link.
As an example, suppose a link representing a methanation process takes
as inputs one unit of hydrogen and 0.5 units of carbon dioxide, and
gives as outputs 0.8 units of methane and 0.2 units of heat. Then
bus0
connects to hydrogen, bus1
connects to carbon dioxide
with efficiency=0.5
(since 0.5 units of carbon dioxide is taken
for each unit of hydrogen), bus2
connects to methane with
efficiency2=0.8
and bus3
to heat with efficiency3=0.2
.
The example Biomass, synthetic fuels and carbon management provides many examples of modelling processes with multiple inputs and outputs using links.
Shapes#
Shapes is of a geopandas dataframe which can be used to store networkrelated geographical data (for plotting, calculating potentials, etc.). The dataframe has the columns geometry, component, idx and type. The columns component, idx and type do not require specific values, but give the user the possibility to store additional information about the shapes.
attribute 
type 
unit 
default 
description 
status 

name 
string 
n/a 
n/a 
Unique name 
Input (required) 
geometry 
geometry 
n/a 
n/a 
Geometry 
Input (optional) 
component 
string 
n/a 
n/a 
Component 
Input (optional) 
idx 
string 
n/a 
n/a 
Name of the component. Should be in component’s index 
Input (optional) 
type 
string 
n/a 
n/a 
Type of geometry 
Input (optional) 
Groups of Components#
In the code components are grouped according to their properties in
sets such as network.one_port_components
and
network.branch_components
.
Oneports share the property that they all connect to a single bus,
i.e. generators, loads, storage units, etc.. They share the attributes
bus
, p_set
, q_set
, p
, q
.
Branches connect two buses. A copy of their attributes can be accessed
as a group by the function network.branches()
. They share the
attributes bus0
, bus1
.
Passive branches are branches whose power flow is not directly controllable, but is determined passively by their impedances and the nodal power imbalances, i.e. lines and transformers.
Controllable branches are branches whose power flow can be controlled by e.g. the LOPF optimisation, i.e. links.
Custom Components#
If you want to define your own components and override the standard
functionality of PyPSA, you can easily override the standard
components by passing pypsa.Network() the arguments
override_components
and override_component_attrs
.
For this network, these will replace the standard definitions in
pypsa.components.components
and
pypsa.components.component_attrs
, which correspond to the
repository CSV files pypsa/components.csv
and
pypsa/component_attrs/*.csv
.
components
is a pandas.DataFrame with the component name
,
list_name
and description
. component_attrs
is a
pypsa.descriptors.Dict of pandas.DataFrame with the attribute
properties for each component. Just follow the formatting for the
standard components.
There are examples for defining new components in the git repository
in examples/new_components/
, including an example of
overriding e.g. network.optimize()
for functionality for
combinedheatandpower (CHP) plants.