GridData Module¶

Module containing PowerGAMA GridData class and sub-classes

Grid data and time-dependent profiles

class powergama.GridData.GridData¶

Class for grid data storage and import

Methods

`branchDistances`([R])	computes branch distance from node coordinates, resuls in km
`branchFromNodeIdx`()	get node indices for branch FROM node
`branchToNodeIdx`()	get node indices for branch TO node
`computePowerFlowMatrices`([baseZ])	Compute and return dc power flow matrices B’ and DA
`dcBranchFromNodeIdx`()	get node indices for dc branch FROM node
`dcBranchToNodeIdx`()	get node indices for dc branch TO node
`getAllAreas`()	Return list of areas included in the grid model
`getAllGeneratorTypes`([sort])	Return list of generator types included in the grid model
`getConsumerAreas`()	List of areas for each consumer
`getConsumersPerArea`()	Returns dictionary with indices of loads within each area
`getDcBranches`()	Returns a list with DC branches in the format [index,from area,to area]
`getDcBranchesAtNode`(nodeIdx, direction)	Indices of all DC branches attached to a particular node
`getFlexibleLoadStorageCapacity`(consumer_indx)	flexible load storage capacity in MWh
`getGeneratorAreas`()	List of areas for each generator
`getGeneratorsAtNode`(nodeIdx)	Indices of all generators attached to a particular node
`getGeneratorsPerAreaAndType`()	Returns dictionary with indices of generators within each area
`getGeneratorsPerType`()	Returns dictionary with indices of generators per type
`getGeneratorsWithPumpAtNode`(nodeIdx)	Indices of all pumps attached to a particular node
`getGeneratorsWithPumpByArea`()	Returns dictionary with indices of generators with pumps within each area
`getIdxBranchesWithFlowConstraints`()	Indices of branches with less than infinite branch capacity
`getIdxBranchesWithLength`()	Indices of branches with specified length
`getIdxConsumersWithFlexibleLoad`()	Indices of all consumers with flexible load
`getIdxDcBranchesWithFlowConstraints`()	Indices of DC branches with less than infinite branch capacity
`getIdxGeneratorsWithNonzeroInflow`()	Indices of all generators with nonzero inflow
`getIdxGeneratorsWithPumping`()	Indices of all generators with pumping capacity
`getIdxGeneratorsWithStorage`()	Indices of all generators with nonzero and non-infinite storage
`getIdxNodesWithLoad`()	Indices of nodes that have load (consumer) attached to them
`getInterAreaBranches`([area_from, area_to, acdc])	Get indices of branches from and/or to specified area(s)
`getLoadsAtNode`(nodeIdx)	Indices of all loads (consumers) attached to a particular node
`getLoadsFlexibleAtNode`(nodeIdx)	Indices of all flexible nodes attached to a particular node
`readGridData`(nodes, ac_branches, …[, …])	Read grid data from files into data variables
`readProfileData`(filename, timerange[, …])	Read profile (timeseries) into numpy arrays
`readSipData`(nodes, branches, generators, …)	Read grid data for investment analysis from files (PowerGIM)
`spreadNodeCoordinates`([radius, inplace])	Spread nodes with identical coordinates in a small circle with radius r
`writeGridDataToFiles`(prefix)	Save data to new input files

getBranchAreas
getDcBranchAreas
numBranches
numConsumers
numDcBranches
numGenerators
numNodes

branchDistances(R=6373.0)¶

computes branch distance from node coordinates, resuls in km

Uses haversine formula

Parameters:	R : radius of the Earth

branchFromNodeIdx()¶: get node indices for branch FROM node

branchToNodeIdx()¶: get node indices for branch TO node

computePowerFlowMatrices(baseZ=1)¶

Compute and return dc power flow matrices B’ and DA

Parameters:	baseZ : float (impedance should already be in pu.) base value for impedance
Returns:	(Bprime, DA) : compressed sparse row matrix

dcBranchFromNodeIdx()¶: get node indices for dc branch FROM node

dcBranchToNodeIdx()¶: get node indices for dc branch TO node

getAllAreas()¶: Return list of areas included in the grid model

getAllGeneratorTypes(sort='fuelcost')¶: Return list of generator types included in the grid model

getBranchAreas()¶

getConsumerAreas()¶: List of areas for each consumer

getConsumersPerArea()¶: Returns dictionary with indices of loads within each area

getDcBranchAreas()¶

getDcBranches()¶: Returns a list with DC branches in the format [index,from area,to area]

getDcBranchesAtNode(nodeIdx, direction)¶: Indices of all DC branches attached to a particular node

getFlexibleLoadStorageCapacity(consumer_indx)¶: flexible load storage capacity in MWh

getGeneratorAreas()¶: List of areas for each generator

getGeneratorsAtNode(nodeIdx)¶: Indices of all generators attached to a particular node

getGeneratorsPerAreaAndType()¶: Returns dictionary with indices of generators within each area

getGeneratorsPerType()¶: Returns dictionary with indices of generators per type

getGeneratorsWithPumpAtNode(nodeIdx)¶: Indices of all pumps attached to a particular node

getGeneratorsWithPumpByArea()¶: Returns dictionary with indices of generators with pumps within each area

getIdxBranchesWithFlowConstraints()¶: Indices of branches with less than infinite branch capacity

getIdxBranchesWithLength()¶: Indices of branches with specified length

getIdxConsumersWithFlexibleLoad()¶: Indices of all consumers with flexible load

getIdxDcBranchesWithFlowConstraints()¶: Indices of DC branches with less than infinite branch capacity

getIdxGeneratorsWithNonzeroInflow()¶: Indices of all generators with nonzero inflow

getIdxGeneratorsWithPumping()¶: Indices of all generators with pumping capacity

getIdxGeneratorsWithStorage()¶: Indices of all generators with nonzero and non-infinite storage

getIdxNodesWithLoad()¶: Indices of nodes that have load (consumer) attached to them

getInterAreaBranches(area_from=None, area_to=None, acdc='ac')¶

Get indices of branches from and/or to specified area(s)

area_from = area from. Use None (default) to leave unspecifie area_to= area to. Use None (default) to leave unspecified acdc = ‘ac’ (default) for ac branches, ‘dc’ for dc branches

getLoadsAtNode(nodeIdx)¶: Indices of all loads (consumers) attached to a particular node

getLoadsFlexibleAtNode(nodeIdx)¶: Indices of all flexible nodes attached to a particular node

keys_powergama = {'branch': {'capacity': None, 'node_from': None, 'node_to': None, 'reactance': None, 'resistance': 0}, 'consumer': {'demand_avg': None, 'demand_ref': None, 'flex_basevalue': 0, 'flex_fraction': 0, 'flex_on_off': 0, 'flex_storage': 0, 'flex_storagelevel_init': 0.5, 'flex_storval_filling': '', 'flex_storval_time': '', 'node': None}, 'dcbranch': {'capacity': None, 'node_from': None, 'node_to': None, 'resistance': 0}, 'generator': {'desc': '', 'fuelcost': None, 'inflow_fac': None, 'inflow_ref': None, 'node': None, 'pmax': None, 'pmin': None, 'pump_cap': 0, 'pump_deadband': 0, 'pump_efficiency': 0, 'storage_cap': 0, 'storage_ini': 0, 'storage_price': 0, 'storval_filling_ref': '', 'storval_time_ref': '', 'type': None}, 'node': {'area': None, 'id': None, 'lat': None, 'lon': None}}¶

keys_sipdata = {'branch': {'capacity': None, 'capacity2': 0, 'cost_scaling': None, 'distance': -1, 'expand': None, 'expand2': None, 'max_newCap': -1, 'node_from': None, 'node_to': None, 'reactance': 0, 'type': None}, 'consumer': {'demand_avg': None, 'demand_ref': None, 'emission_cap': -1, 'node': None}, 'dcbranch': {'capacity': 0, 'node_from': '', 'node_to': '', 'resistance': 0}, 'generator': {'cost_scaling': 1, 'desc': '', 'expand': None, 'expand2': None, 'fuelcost': None, 'fuelcost_ref': None, 'inflow_fac': None, 'inflow_ref': None, 'node': None, 'p_maxNew': -1, 'pavg': 0, 'pmax': None, 'pmax2': 0, 'pmin': None, 'type': None}, 'node': {'area': None, 'cost_scaling': None, 'existing': None, 'id': None, 'lat': None, 'lon': None, 'offshore': None, 'type': None}}¶

numBranches()¶

numConsumers()¶

numDcBranches()¶

numGenerators()¶

numNodes()¶

readGridData(nodes, ac_branches, dc_branches, generators, consumers, remove_extra_columns=False)¶: Read grid data from files into data variables

readProfileData(filename, timerange, storagevalue_filling=None, storagevalue_time=None, timedelta=1.0)¶: Read profile (timeseries) into numpy arrays

readSipData(nodes, branches, generators, consumers)¶

Read grid data for investment analysis from files (PowerGIM)

This is used with the grid investment module (PowerGIM)

time-series data may be used for consumer demand generator inflow (e.g. solar and wind) generator fuelcost (e.g. one generator with fuelcost = power price)

spreadNodeCoordinates(radius=0.01, inplace=False)¶

Spread nodes with identical coordinates in a small circle with radius r

Parameters:	radius : float radius in degrees for the size of the spread inplace : boolean if true, update GridData object
Returns:	coords : array lat,lon pandas array for nodes

writeGridDataToFiles(prefix)¶: Save data to new input files