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 x-port 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

2-winding transformer.

passive_branch

TransformerType

transformer_types

Standard 2-winding 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 point-to-point DC connection OR as a lossy energy converter. NB: for a lossless bi-directional 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 nominal-energy-to-nominal-power 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

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.

Time-varying 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 Time-varying 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 time-dependent series quantities are indexed by network.snapshots. To reset the snapshots, call network.set_snapshots(new).

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 network.pf() is called without a snapshot argument.

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)

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 time-dependent bus information compiled by PyPSA from inputs. Dictionary keys are time-dependent 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 time-dependent line information compiled by PyPSA from inputs. Dictionary keys are time-dependent 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.): time-dependent component information compiled by PyPSA from inputs. Dictionary keys are time-dependent 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

Sub-Network#

Sub-networks are determined by PyPSA and should not be entered by the user.

Sub-networks 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” sub-networks, these correspond to synchronous areas. Only “AC” and “DC” sub-networks can contain passive branches; all other sub-networks must contain a single isolated bus.

The power flow in sub-networks is determined by the passive flow through passive branches due to the impedances of the passive branches.

Sub-Network 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 sub-network in list of sub-networks.

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).

_images/buses.png

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

sub_network

string

n/a

n/a

Name of connected sub-network 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

0

active power at bus (positive if net generation at bus)

Output

q

series

MVar

0

reactive power (positive if net generation at bus)

Output

v_mag_pu

series

per unit

1

Voltage magnitude, per unit of v_nom

Output

v_ang

series

radians

0

Voltage angle

Output

marginal_price

series

currency/MWh

0

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 CO2-tonnes-equivalent 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 primary-energy-related 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 right-hand-side of constraint for optimisation period. For a CO2 constraint, this would be tonnes of CO2-equivalent 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 carrier-type 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 time-varying 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 de-rating factor.

Generators with time-varying limits are like variable weather-dependent 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_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

0

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 feed-in; for conventional generators it represents a minimal dispatch). Note that if comittable is False and p_min_pu > 0, this represents a must-run 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

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 optimization

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 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

0

Stand-by 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 non-zero.

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 non-zero.

Input (optional)

ramp_limit_up

float

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

float

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

0

active power at bus (positive if net generation)

Output

q

series

MVar

0

reactive power (positive if net generation)

Output

p_nom_opt

float

MW

0

Optimised nominal power.

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

0

Shadow price of upper p_nom limit

Output

mu_lower

series

currency/MWh

0

Shadow price of lower p_nom limit

Output

mu_p_set

series

currency/MWh

0

Shadow price of fixed power generation p_set

Output

mu_ramp_limit_up

series

currency/MWh

0

Shadow price of upper ramp up limit

Output

mu_ramp_limit_down

series

currency/MWh

0

Shadow price of lower ramp down limit

Output

Storage Unit#

Storage units attach to a single bus and are used for inter-temporal power shifting. Each storage unit has a time-varying 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_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

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_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

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 voltage-dependent 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 non-zero 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 non-zero for the non-linear power flow. Ignored if type defined.

Input (required)

r

float

Ohm

0

Series resistance, must be non-zero for DC branch in linear power flow. Series impedance \(z = r + jx\) must be non-zero for the non-linear 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_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 n-1 factor, or can be time-varying to represent weather-dependent 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 sub-network 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

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

mu_lower

series

currency/MVA

0

Shadow price of lower s_nom limit -F leq f. Always non-negative.

Output

mu_upper

series

currency/MVA

0

Shadow price of upper s_nom limit f leq F. Always non-negative.

Output

Line Types#

Standard line types with per length values for impedances.

If for a line the attribute “type” is non-empty, 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 cross-section

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

149-AL1/24-ST1A 10.0

0.194

0.315

11.25

0.47

ol

149

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

149-AL1/24-ST1A 110.0

0.194

0.41

8.75

0.47

ol

149

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

149-AL1/24-ST1A 20.0

0.194

0.337

10.5

0.47

ol

149

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

15-AL1/3-ST1A 0.4

1.8769

0.35

11

0.105

ol

16

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

184-AL1/30-ST1A 110.0

0.1571

0.4

8.8

0.535

ol

184

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

184-AL1/30-ST1A 20.0

0.1571

0.33

10.75

0.535

ol

184

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

24-AL1/4-ST1A 0.4

1.2012

0.335

11.25

0.14

ol

24

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

243-AL1/39-ST1A 110.0

0.1188

0.39

9

0.645

ol

243

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

243-AL1/39-ST1A 20.0

0.1188

0.32

11

0.645

ol

243

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

305-AL1/39-ST1A 110.0

0.0949

0.38

9.2

0.74

ol

305

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

48-AL1/8-ST1A 0.4

0.5939

0.3

12.2

0.21

ol

48

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

48-AL1/8-ST1A 10.0

0.5939

0.35

10.1

0.21

ol

48

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

48-AL1/8-ST1A 20.0

0.5939

0.372

9.5

0.21

ol

48

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

490-AL1/64-ST1A 220.0

0.059

0.285

10

0.96

ol

490

pandapower

490-AL1/64-ST1A 380.0

0.059

0.253

11

0.96

ol

490

pandapower

94-AL1/15-ST1A 0.4

0.306

0.29

13.2

0.35

ol

94

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

94-AL1/15-ST1A 10.0

0.306

0.33

10.75

0.35

ol

94

pandapower;Heuck et al. Elektrische Energieversorgung 8. Auflage (2010); Vierweg+Teubner (2013)

94-AL1/15-ST1A 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 2-bundle 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 3-bundle 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 4-bundle 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 4-bundle 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,”ENTSO-E AISBL, Brussels, Belgium, Tech. Rep., 2011. P.21-22

HVDC Oil filled 1400

0.00264

0.000001

10000

2.8

3000

Regional Group North Sea, “Offshore Transmission Technology,”ENTSO-E AISBL, Brussels, Belgium, Tech. Rep., 2011. P.19-20

Transformer#

Transformers represent 2-winding 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 2-winding 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 non-zero for AC branch in linear power flow. Series impedance \(z = r + jx\) must be non-zero for the non-linear 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 non-zero for DC branch in linear power flow. Series impedance \(z = r + jx\) must be non-zero for the non-linear 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_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 high-voltage) 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 sub-network 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

mu_lower

series

currency/MVA

0

Shadow price of lower s_nom limit -F leq f. Always non-negative.

Output

mu_upper

series

currency/MVA

0

Shadow price of upper s_nom limit f leq F. Always non-negative.

Output

Transformer Types#

Standard 2-winding transformer types.

If for a transformer the attribute “type” is non-empty, 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 high-voltage) 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

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.

One-ports 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 combined-heat-and-power (CHP) plants.