def __init__(self, esM, name, commodity, losses=0, distances=None,
hasCapacityVariable=True, capacityVariableDomain='continuous', capacityPerPlantUnit=1,
hasIsBuiltBinaryVariable=False, bigM=None,
operationRateMax=None, operationRateFix=None, tsaWeight=1,
locationalEligibility=None, capacityMin=None, capacityMax=None, sharedPotentialID=None,
capacityFix=None, isBuiltFix=None,
investPerCapacity=0, investIfBuilt=0, opexPerOperation=0, opexPerCapacity=0,
opexIfBuilt=0, interestRate=0.08, economicLifetime=10):
"""
Constructor for creating an Transmission class instance.
The Transmission component specific input arguments are described below. The general component
input arguments are described in the Component class.
**Required arguments:**
:param commodity: to the component related commodity.
:type commodity: string
**Default arguments:**
:param losses: relative losses per lengthUnit (lengthUnit as specified in the energy system model) in
percentage of the commodity flow. This loss factor can capture simple linear losses
trans_in_ij=(1-losses*distance)*trans_out_ij (with trans being the commodity flow at a certain point in
time and i and j being locations in the energy system). The losses can either be given as a float or a
Pandas DataFrame with location specific values.
|br| * the default value is 0
:type losses: positive float (0 <= float <= 1) or Pandas DataFrame with positive values
(0 <= float <= 1). The row and column indices of the DataFrame have to equal the in the energy
system model specified locations.
:param distances: distances between locations given in the lengthUnit (lengthUnit as specified in
the energy system model).
|br| * the default value is None
:type distances: positive float (>= 0) or Pandas DataFrame with positive values (>= 0). The row and
column indices of the DataFrame have to equal the in the energy system model specified locations.
:param operationRateMax: if specified, indicates a maximum operation rate for all possible connections
(both directions) of the transmission component at each time step by a positive float. If
hasCapacityVariable is set to True, the values are given relative to the installed capacities (i.e.
a value of 1 indicates a utilization of 100% of the capacity). If hasCapacityVariable
is set to False, the values are given as absolute values in form of the commodityUnit,
referring to the transmitted commodity (before considering losses) during one time step.
|br| * the default value is None
:type operationRateMax: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices are combinations
of locations (as defined in the energy system model), separated by a underscore (e.g.
"location1_location2"). The first location indicates where the commodity is coming from. The second
one location indicates where the commodity is going too. If a flow is specified from location i to
location j, it also has to be specified from j to i.
:param operationRateFix: if specified, indicates a fixed operation rate for all possible connections
(both directions) of the transmission component at each time step by a positive float. If
hasCapacityVariable is set to True, the values are given relative to the installed capacities (i.e.
a value of 1 indicates a utilization of 100% of the capacity). If hasCapacityVariable
is set to False, the values are given as absolute values in form of the commodityUnit,
referring to the transmitted commodity (before considering losses) during one time step.
|br| * the default value is None
:type operationRateFix: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices are combinations
of locations (as defined in the energy system model), separated by a underscore (e.g.
"location1_location2"). The first location indicates where the commodity is coming from. The second
one location indicates where the commodity is going too. If a flow is specified from location i to
location j, it also has to be specified from j to i.
:param tsaWeight: weight with which the time series of the component should be considered when applying
time series aggregation.
|br| * the default value is 1
:type tsaWeight: positive (>= 0) float
:param opexPerOperation: describes the cost for one unit of the operation.
The cost which is directly proportional to the operation of the component is obtained by multiplying
the opexPerOperation parameter with the annual sum of the operational time series of the components.
The opexPerOperation can either be given as a float or a Pandas DataFrame with location specific values.
The cost unit in which the parameter is given has to match the one specified in the energy
system model (e.g. Euro, Dollar, 1e6 Euro).
|br| * the default value is 0
:type opexPerOperation: positive (>=0) float or Pandas DataFrame with positive (>=0) values.
The row and column indices of the DataFrame have to equal the in the energy system model
specified locations.
"""
# TODO add unit checks
# Preprocess two-dimensional data
self.locationalEligibility = utils.preprocess2dimData(locationalEligibility)
self.capacityMax = utils.preprocess2dimData(capacityMax)
self.capacityFix = utils.preprocess2dimData(capacityFix)
self.isBuiltFix = utils.preprocess2dimData(isBuiltFix)
# Set locational eligibility
operationTimeSeries = operationRateFix if operationRateFix is not None else operationRateMax
self.locationalEligibility = \
utils.setLocationalEligibility(esM, self.locationalEligibility, self.capacityMax, self.capacityFix,
self.isBuiltFix, hasCapacityVariable, operationTimeSeries, '2dim')
self._mapC, self._mapL, self._mapI = {}, {}, {}
for loc1 in esM.locations:
for loc2 in esM.locations:
if loc1 + '_' + loc2 in self.locationalEligibility.index:
if self.locationalEligibility[loc1 + '_' + loc2] == 0:
self.locationalEligibility[loc1 + '_' + loc2].drop(inplace=True)
self._mapC.update({loc1 + '_' + loc2: (loc1, loc2)})
self._mapL.setdefault(loc1, {}).update({loc2: loc1 + '_' + loc2})
self._mapI.update({loc1 + '_' + loc2: loc2 + '_' + loc1})
self.capacityMin = utils.preprocess2dimData(capacityMin, self._mapC)
self.investPerCapacity = utils.preprocess2dimData(investPerCapacity, self._mapC)
self.investIfBuilt = utils.preprocess2dimData(investIfBuilt, self._mapC)
self.opexPerCapacity = utils.preprocess2dimData(opexPerCapacity, self._mapC)
self.opexIfBuilt = utils.preprocess2dimData(opexIfBuilt, self._mapC)
self.interestRate = utils.preprocess2dimData(interestRate, self._mapC)
self.economicLifetime = utils.preprocess2dimData(economicLifetime, self._mapC)
Component. __init__(self, esM, name, dimension='2dim', hasCapacityVariable=hasCapacityVariable,
capacityVariableDomain=capacityVariableDomain, capacityPerPlantUnit=capacityPerPlantUnit,
hasIsBuiltBinaryVariable=hasIsBuiltBinaryVariable, bigM=bigM,
locationalEligibility=self.locationalEligibility, capacityMin=self.capacityMin,
capacityMax=self.capacityMax, sharedPotentialID=sharedPotentialID,
capacityFix=self.capacityFix, isBuiltFix=self.isBuiltFix,
investPerCapacity=self.investPerCapacity, investIfBuilt=self.investIfBuilt,
opexPerCapacity=self.opexPerCapacity, opexIfBuilt=self.opexIfBuilt,
interestRate=self.interestRate, economicLifetime=self.economicLifetime)
# Set general component data
utils.checkCommodities(esM, {commodity})
self.commodity, self.commodityUnit = commodity, esM.commodityUnitsDict[commodity]
self.distances = utils.preprocess2dimData(distances, self._mapC)
self.losses = utils.preprocess2dimData(losses, self._mapC)
self.distances = utils.checkAndSetDistances(self.distances, self.locationalEligibility, esM)
self.losses = utils.checkAndSetTransmissionLosses(self.losses, self.distances, self.locationalEligibility)
self.modelingClass = TransmissionModel
# Set additional economic data
self.opexPerOperation = utils.checkAndSetCostParameter(esM, name, opexPerOperation, '2dim',
self.locationalEligibility)
# Set location-specific operation parameters
if operationRateMax is not None and operationRateFix is not None:
operationRateMax = None
if esM.verbose < 2:
warnings.warn('If operationRateFix is specified, the operationRateMax parameter is not required.\n' +
'The operationRateMax time series was set to None.')
self.fullOperationRateMax = utils.checkAndSetTimeSeries(esM, operationRateMax, self.locationalEligibility)
self.aggregatedOperationRateMax, self.operationRateMax = None, None
self.fullOperationRateFix = utils.checkAndSetTimeSeries(esM, operationRateFix, self.locationalEligibility)
self.aggregatedOperationRateFix, self.operationRateFix = None, None
utils.isPositiveNumber(tsaWeight)
self.tsaWeight = tsaWeight
def __init__(self,
esM,
name,
physicalUnit,
commodityConversionFactors,
hasCapacityVariable=True,
capacityVariableDomain='continuous',
capacityPerPlantUnit=1,
linkedConversionCapacityID=None,
hasIsBuiltBinaryVariable=False,
bigM=None,
operationRateMax=None,
operationRateFix=None,
tsaWeight=1,
locationalEligibility=None,
capacityMin=None,
capacityMax=None,
partLoadMin=None,
sharedPotentialID=None,
capacityFix=None,
isBuiltFix=None,
investPerCapacity=0,
investIfBuilt=0,
opexPerOperation=0,
opexPerCapacity=0,
opexIfBuilt=0,
QPcostScale=0,
interestRate=0.08,
economicLifetime=10,
technicalLifetime=None,
yearlyFullLoadHoursMin=None,
yearlyFullLoadHoursMax=None):
# TODO: allow that the time series data or min/max/fixCapacity/eligibility is only specified for
# TODO: eligible locations
"""
Constructor for creating an Conversion class instance. Capacities are given in the physical unit
of the plants.
The Conversion component specific input arguments are described below. The general component
input arguments are described in the Component class.
**Required arguments:**
:param physicalUnit: reference physical unit of the plants to which maximum capacity limitations,
cost parameters and the operation time series refer to.
:type physicalUnit: string
:param commodityConversionFactors: conversion factors with which commodities are converted into each
other with one unit of operation (dictionary). Each commodity which is converted in this component
is indicated by a string in this dictionary. The conversion factor related to this commodity is
given as a float. A negative value indicates that the commodity is consumed. A positive value
indicates that the commodity is produced. Check unit consistency when specifying this parameter!
Examples:\n
* An electrolyzer converts, simply put, electricity into hydrogen with an electrical efficiency
of 70%. The physicalUnit is given as GW_electric, the unit for the 'electricity' commodity is
given in GW_electric and the 'hydrogen' commodity is given in GW_hydrogen_lowerHeatingValue
-> the commodityConversionFactors are defined as {'electricity':-1,'hydrogen':0.7}.
* A fuel cell converts, simply put, hydrogen into electricity with an efficiency of 60%.\n
The physicalUnit is given as GW_electric, the unit for the 'electricity' commodity is given in
GW_electric and the 'hydrogen' commodity is given in GW_hydrogen_lowerHeatingValue
-> the commodityConversionFactors are defined as {'electricity':1,'hydrogen':-1/0.6}.\n
:type commodityConversionFactors: dictionary, assigns commodities (string) to a conversion factors
(float)
**Default arguments:**
:param linkedConversionCapacityID: if specifies, indicates that all conversion components with the
same ID have to have the same capacity.
|br| * the default value is None
:type linkedConversionCapacityID: string
:param operationRateMax: if specified, indicates a maximum operation rate for each location and each time
step by a positive float. If hasCapacityVariable is set to True, the values are given relative
to the installed capacities (i.e. a value of 1 indicates a utilization of 100% of the
capacity). If hasCapacityVariable is set to False, the values are given as absolute values in form
of the physicalUnit of the plant for each time step.
|br| * the default value is None
:type operationRateMax: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices have to match the
in the energy system model specified locations.
:param operationRateFix: if specified, indicates a fixed operation rate for each location and each time
step by a positive float. If hasCapacityVariable is set to True, the values are given relative
to the installed capacities (i.e. a value of 1 indicates a utilization of 100% of the
capacity). If hasCapacityVariable is set to False, the values are given as absolute values in form
of the physicalUnit of the plant for each time step.
|br| * the default value is None
:type operationRateFix: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices have to match the
in the energy system model specified locations.
:param tsaWeight: weight with which the time series of the component should be considered when applying
time series aggregation.
|br| * the default value is 1
:type tsaWeight: positive (>= 0) float
:param opexPerOperation: describes the cost for one unit of the operation. The cost which is
directly proportional to the operation of the component is obtained by multiplying
the opexPerOperation parameter with the annual sum of the operational time series of the components.
The opexPerOperation can either be given as a float or a Pandas Series with location specific values.
The cost unit in which the parameter is given has to match the one specified in the energy
system model (e.g. Euro, Dollar, 1e6 Euro).
|br| * the default value is 0
:type opexPerOperation: positive (>=0) float or Pandas Series with positive (>=0) values.
The indices of the series have to equal the in the energy system model specified locations.
"""
Component.__init__(self,
esM,
name,
dimension='1dim',
hasCapacityVariable=hasCapacityVariable,
capacityVariableDomain=capacityVariableDomain,
capacityPerPlantUnit=capacityPerPlantUnit,
hasIsBuiltBinaryVariable=hasIsBuiltBinaryVariable,
bigM=bigM,
locationalEligibility=locationalEligibility,
capacityMin=capacityMin,
capacityMax=capacityMax,
partLoadMin=partLoadMin,
sharedPotentialID=sharedPotentialID,
capacityFix=capacityFix,
isBuiltFix=isBuiltFix,
investPerCapacity=investPerCapacity,
investIfBuilt=investIfBuilt,
opexPerCapacity=opexPerCapacity,
opexIfBuilt=opexIfBuilt,
QPcostScale=QPcostScale,
interestRate=interestRate,
economicLifetime=economicLifetime,
technicalLifetime=technicalLifetime,
yearlyFullLoadHoursMin=yearlyFullLoadHoursMin,
yearlyFullLoadHoursMax=yearlyFullLoadHoursMax)
# Set general conversion data: commodityConversionFactors, physicalUnit, linkedConversionCapacityID
utils.checkCommodities(esM, set(commodityConversionFactors.keys()))
utils.checkCommodityUnits(esM, physicalUnit)
if linkedConversionCapacityID is not None:
utils.isString(linkedConversionCapacityID)
self.commodityConversionFactors = commodityConversionFactors
self.physicalUnit = physicalUnit
self.modelingClass = ConversionModel
self.linkedConversionCapacityID = linkedConversionCapacityID
# Set additional economic data: opexPerOperation
self.opexPerOperation = utils.checkAndSetCostParameter(
esM, name, opexPerOperation, '1dim', locationalEligibility)
# Set location-specific operation parameters: operationRateMax or operationRateFix, tsaweight
if operationRateMax is not None and operationRateFix is not None:
operationRateMax = None
if esM.verbose < 2:
warnings.warn(
'If operationRateFix is specified, the operationRateMax parameter is not required.\n'
+ 'The operationRateMax time series was set to None.')
self.fullOperationRateMax = utils.checkAndSetTimeSeries(
esM, operationRateMax, locationalEligibility)
self.aggregatedOperationRateMax, self.operationRateMax = None, None
self.fullOperationRateFix = utils.checkAndSetTimeSeries(
esM, operationRateFix, locationalEligibility)
self.aggregatedOperationRateFix, self.operationRateFix = None, None
if self.partLoadMin is not None:
if self.fullOperationRateMax is not None:
if ((self.fullOperationRateMax > 0) &
(self.fullOperationRateMax < self.partLoadMin)
).any().any():
raise ValueError(
'"operationRateMax" needs to be higher than "partLoadMin" or 0 for component '
+ name)
if self.fullOperationRateFix is not None:
if ((self.fullOperationRateFix > 0) &
(self.fullOperationRateFix < self.partLoadMin)
).any().any():
raise ValueError(
'"fullOperationRateFix" needs to be higher than "partLoadMin" or 0 for component '
+ name)
utils.isPositiveNumber(tsaWeight)
self.tsaWeight = tsaWeight
# Set locational eligibility
operationTimeSeries = self.fullOperationRateFix if self.fullOperationRateFix is not None \
else self.fullOperationRateMax
self.locationalEligibility = \
utils.setLocationalEligibility(esM, self.locationalEligibility, self.capacityMax, self.capacityFix,
self.isBuiltFix, self.hasCapacityVariable, operationTimeSeries)
def __init__(self,
esM,
name,
commodity,
hasCapacityVariable,
capacityVariableDomain='continuous',
capacityPerPlantUnit=1,
hasIsBuiltBinaryVariable=False,
bigM=None,
operationRateMax=None,
operationRateFix=None,
tsaWeight=1,
commodityLimitID=None,
yearlyLimit=None,
locationalEligibility=None,
capacityMin=None,
capacityMax=None,
sharedPotentialID=None,
capacityFix=None,
isBuiltFix=None,
investPerCapacity=0,
investIfBuilt=0,
opexPerOperation=0,
commodityCost=0,
commodityRevenue=0,
commodityCostTimeSeries=None,
commodityRevenueTimeSeries=None,
opexPerCapacity=0,
opexIfBuilt=0,
interestRate=0.08,
economicLifetime=10):
"""
Constructor for creating an Source class instance.
The Source component specific input arguments are described below. The general component
input arguments are described in the Component class.
Note: the Sink class inherits from the Source class and is initialized with the same parameter set.
**Required arguments:**
:param commodity: to the component related commodity.
:type commodity: string
:param hasCapacityVariable: specifies if the component should be modeled with a capacity or not.
Examples:\n
* A wind turbine has a capacity given in GW_electric -> hasCapacityVariable is True.
* Emitting CO2 into the environment is not per se limited by a capacity ->
hasCapaityVariable is False.\n
:type hasCapacityVariable: boolean
**Default arguments:**
:param operationRateMax: if specified, indicates a maximum operation rate for each location and each time
step by a positive float. If hasCapacityVariable is set to True, the values are given relative
to the installed capacities (i.e. a value of 1 indicates a utilization of 100% of the
capacity). If hasCapacityVariable is set to False, the values are given as absolute values in form
of the commodityUnit for each time step.
|br| * the default value is None
:type operationRateMax: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices have to equal the
in the energy system model specified locations. The data in ineligible locations are set to zero.
:param operationRateFix: if specified, indicates a fixed operation rate for each location and each time
step by a positive float. If hasCapacityVariable is set to True, the values are given relative
to the installed capacities (i.e. a value of 1 indicates a utilization of 100% of the
capacity). If hasCapacityVariable is set to False, the values are given as absolute values in form
of the commodityUnit for each time step.
|br| * the default value is None
:type operationRateFix: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices have to equal the
in the energy system model specified locations. The data in ineligible locations are set to zero.
:param commodityCostTimeSeries: if specified, indicates commodity cost rates for each location and each
time step by a positive float. The values are given as specific values relative to the commodityUnit
for each time step.
|br| * the default value is None
:type commodityCostTimeSeries: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices have to equal the
in the energy system model specified locations. The data in ineligible locations are set to zero.
:param commodityRevenueTimeSeries: if specified, indicates commodity revenue rate for each location and
each time step by a positive float. The values are given as specific values relative to the
commodityUnit for each time step.
|br| * the default value is None
:type commodityRevenueTimeSeries: None or Pandas DataFrame with positive (>= 0) entries. The row indices
have to match the in the energy system model specified time steps. The column indices have to equal
the in the energy system model specified locations. The data in ineligible locations are set to zero.
:param tsaWeight: weight with which the time series of the component should be considered when applying
time series aggregation.
|br| * the default value is 1
:type tsaWeight: positive (>= 0) float
:param commodityLimitID: can be specified to limit an annual commodity import/export over the
energySystemModel's boundaries for one or multiple Source/Sink components. If the same ID
is used in multiple components, the sum of all imports and exports is considered. If a
commoditiyLimitID is specified, the yearlyLimit parameters has to be set as well.
|br| * the default value is None
:type commodityLimitID: string
:param yearlyLimit: if specified, indicates a yearly import/export commodity limit for all components with
the same commodityLimitID. If positive, the commodity flow leaving the energySystemModel is
limited. If negative, the commodity flow entering the energySystemModel is limited. If a
yearlyLimit is specified, the commoditiyLimitID parameters has to be set as well.
Examples:\n
* CO2 can be emitted in power plants by burning natural gas or coal. The CO2 which goes into
the atmosphere over the energy system's boundaries is modelled as a Sink. CO2 can also be a
Source taken directly from the atmosphere (over the energy system's boundaries) for a
methanation process. The commodityUnit for CO2 is tonnes_CO2. Overall, +XY tonnes_CO2 are
allowed to be emitted during the year. All Sources/Sinks producing or consuming CO2 over the
energy system's boundaries have the same commodityLimitID and the same yearlyLimit of +XY.
* The maximum annual import of a certain chemical (commodityUnit tonnes_chem) is limited to
XY tonnes_chem. The Source component modeling this import has a commodityLimitID
"chemicalComponentLimitID" and a yearlyLimit of -XY.\n
|br| * the default value is None
:type yearlyLimit: float
:param opexPerOperation: describes the cost for one unit of the operation. The cost which is directly
proportional to the operation of the component is obtained by multiplying the opexPerOperation parameter
with the annual sum of the operational time series of the components.
The opexPerOperation can either be given as a float or a Pandas Series with location specific values.
The cost unit in which the parameter is given has to match the one specified in the energy
system model (e.g. Euro, Dollar, 1e6 Euro).
|br| * the default value is 0
:type opexPerOperation: positive (>=0) float or Pandas Series with positive (>=0) values.
The indices of the series have to equal the in the energy system model specified locations.
:param commodityCost: describes the cost value of one operation´s unit of the component.
The cost which is directly proportional to the operation of the component
is obtained by multiplying the commodityCost parameter with the annual sum of the
time series of the components. The commodityCost can either be given as a
float or a Pandas Series with location specific values.
The cost unit in which the parameter is given has to match the one specified in the energy
system model (e.g. Euro, Dollar, 1e6 Euro).
Example:\n
* In a national energy system, natural gas could be purchased from another country with a
certain cost.\n
|br| * the default value is 0
:type commodityCost: positive (>=0) float or Pandas Series with positive (>=0) values.
The indices of the series have to equal the in the energy system model specified locations.
:param commodityRevenue: describes the revenue of one operation´s unit of the component.
The revenue which is directly proportional to the operation of the component
is obtained by multiplying the commodityRevenue parameter with the annual sum of the
time series of the components. The commodityRevenue can either be given as a
float or a Pandas Series with location specific values.
The cost unit in which the parameter is given has to match the one specified in the energy
system model (e.g. Euro, Dollar, 1e6 Euro).
Example:\n
* Modeling a PV electricity feed-in tariff for a household\n
|br| * the default value is 0
:type commodityRevenue: positive (>=0) float or Pandas Series with positive (>=0) values.
The indices of the series have to equal the in the energy system model specified locations.
"""
Component.__init__(self,
esM,
name,
dimension='1dim',
hasCapacityVariable=hasCapacityVariable,
capacityVariableDomain=capacityVariableDomain,
capacityPerPlantUnit=capacityPerPlantUnit,
hasIsBuiltBinaryVariable=hasIsBuiltBinaryVariable,
bigM=bigM,
locationalEligibility=locationalEligibility,
capacityMin=capacityMin,
capacityMax=capacityMax,
sharedPotentialID=sharedPotentialID,
capacityFix=capacityFix,
isBuiltFix=isBuiltFix,
investPerCapacity=investPerCapacity,
investIfBuilt=investIfBuilt,
opexPerCapacity=opexPerCapacity,
opexIfBuilt=opexIfBuilt,
interestRate=interestRate,
economicLifetime=economicLifetime)
# Set general source/sink data: ID and yearly limit
utils.isEnergySystemModelInstance(esM), utils.checkCommodities(
esM, {commodity})
self.commodity, self.commodityUnit = commodity, esM.commodityUnitsDict[
commodity]
# TODO check value and type correctness
self.commodityLimitID, self.yearlyLimit = commodityLimitID, yearlyLimit
self.sign = 1
self.modelingClass = SourceSinkModel
# Set additional economic data: opexPerOperation, commodityCost, commodityRevenue
self.opexPerOperation = utils.checkAndSetCostParameter(
esM, name, opexPerOperation, '1dim', locationalEligibility)
self.commodityCost = utils.checkAndSetCostParameter(
esM, name, commodityCost, '1dim', locationalEligibility)
self.commodityRevenue = utils.checkAndSetCostParameter(
esM, name, commodityRevenue, '1dim', locationalEligibility)
self.fullCommodityCostTimeSeries = \
utils.checkAndSetTimeSeriesCostParameter(esM, name, commodityCostTimeSeries, locationalEligibility)
self.aggregatedCommodityCostTimeSeries, self.commodityCostTimeSeries = None, None
self.fullCommodityRevenueTimeSeries = \
utils.checkAndSetTimeSeriesCostParameter(esM, name, commodityRevenueTimeSeries, locationalEligibility)
self.aggregatedCommodityRevenueTimeSeries, self.commodityRevenueTimeSeries = None, None
# Set location-specific operation parameters: operationRateMax or operationRateFix, tsaweight
if operationRateMax is not None and operationRateFix is not None:
operationRateMax = None
if esM.verbose < 2:
warnings.warn(
'If operationRateFix is specified, the operationRateMax parameter is not required.\n'
+ 'The operationRateMax time series was set to None.')
self.fullOperationRateMax = utils.checkAndSetTimeSeries(
esM, operationRateMax, locationalEligibility)
self.aggregatedOperationRateMax, self.operationRateMax = None, None
self.fullOperationRateFix = utils.checkAndSetTimeSeries(
esM, operationRateFix, locationalEligibility)
self.aggregatedOperationRateFix, self.operationRateFix = None, None
utils.isPositiveNumber(tsaWeight)
self.tsaWeight = tsaWeight
# Set locational eligibility
operationTimeSeries = self.fullOperationRateFix if self.fullOperationRateFix is not None \
else self.fullOperationRateMax
self.locationalEligibility = \
utils.setLocationalEligibility(esM, self.locationalEligibility, self.capacityMax, self.capacityFix,
self.isBuiltFix, self.hasCapacityVariable, operationTimeSeries)
def __init__(self,
esM,
name,
commodity,
stateOfChargeOpRateMax=None,
stateOfChargeOpRateFix=None,
opexPerChargeOpTimeSeries=None,
stateOfChargeTsaWeight=1,
opexChargeOpTsaWeight=1,
**kwargs):
"""
Constructor for creating an StorageExt class instance.
The StorageExt component specific input arguments are described below. The Storage component specific
input arguments are described in the Storage class and the general component input arguments are described in
the Component class.
**Default arguments:**
:param stateOfChargeOpRateMax: if specified, indicates a maximum state of charge for each location and
each time step by a positive float. If hasCapacityVariable is set to True, the values are given
relative to the installed capacities (i.e. a value of 1 indicates a utilization of
100% of the capacity). If hasCapacityVariable is set to False, the values are given as absolute
values in form of the commodityUnit, referring to the commodity stored in the component at the
beginning of one time step.
|br| * the default value is None
:type stateOfChargeOpRateMax: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices have to match the
in the energy system model specified locations.
:param stateOfChargeOpRateFix: if specified, indicates a fixed state of charge for each location and
each time step by a positive float. If hasCapacityVariable is set to True, the values are given
relative to the installed capacities (i.e. a value of 1 indicates a utilization of
100% of the capacity). If hasCapacityVariable is set to False, the values are given as absolute
values in form of the commodityUnit, referring to the commodity stored in the component at the
beginning of one time step.
|br| * the default value is None
:type stateOfChargeOpRateFix: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices have to match the
in the energy system model specified locations.
:param stateOfChargeTsaWeight: weight with which the stateOfChargeOpRate (max/fix) time series of the
component should be considered when applying time series aggregation.
|br| * the default value is 1
:type stateOfChargeTsaWeight: positive (>= 0) float
"""
Storage.__init__(self, esM, name, commodity, **kwargs)
self.modelingClass = StorageExtModel
# Set location-specific operation parameters (charging rate, discharging rate, state of charge rate)
# and time series aggregation weighting factor
self.stateOfChargeOpRateFix = stateOfChargeOpRateFix
self.stateOfChargeOpRateMax = stateOfChargeOpRateMax
# The i-th state of charge (SOC) refers to the SOC before the i-th time step
if stateOfChargeOpRateMax is not None and stateOfChargeOpRateFix is not None:
stateOfChargeOpRateMax = None
if esM.verbose < 2:
warnings.warn(
"If stateOfChargeOpRateFix is specified, the stateOfChargeOpRateMax parameter is not +"
"required.\nThe stateOfChargeOpRateMax time series was set to None."
)
if (stateOfChargeOpRateMax is not None or stateOfChargeOpRateFix
is not None) and not self.doPreciseTsaModeling:
self.doPreciseTsaModeling = True
if esM.verbose < 2:
warnings.warn(
"Warning only relevant when time series aggregation is used in optimization:\n"
+
"If stateOfChargeOpRateFix or the stateOfChargeOpRateMax parameter are specified,\n"
+ "the modeling is set to precise.")
if stateOfChargeOpRateMax is not None:
if esM.verbose < 2:
warnings.warn(
"Warning only relevant when time series aggregation is used in optimization:\n"
+
"Setting the stateOfChargeOpRateMax parameter might lead to unwanted modeling behavior\n"
+ "and should be handled with caution.")
if stateOfChargeOpRateFix is not None and not self.isPeriodicalStorage:
self.isPeriodicalStorage = True
if esM.verbose < 2:
warnings.warn(
"Warning only relevant when time series aggregation is used in optimization:\n"
+
"If the stateOfChargeOpRateFix parameter is specified, the storage\n"
+ "is set to isPeriodicalStorage).")
self.fullStateOfChargeOpRateMax = utils.checkAndSetTimeSeries(
esM, name, stateOfChargeOpRateMax, self.locationalEligibility)
self.aggregatedStateOfChargeOpRateMax, self.processedStateOfChargeOpRateMax = (
None,
None,
)
self.fullStateOfChargeOpRateFix = utils.checkAndSetTimeSeries(
esM, name, stateOfChargeOpRateFix, self.locationalEligibility)
self.aggregatedStateOfChargeOpRateFix, self.processedStateOfChargeOpRateFix = (
None,
None,
)
self.opexPerChargeOpTimeSeries = opexPerChargeOpTimeSeries
self.fullOpexPerChargeOpTimeSeries = utils.checkAndSetTimeSeries(
esM, name, opexPerChargeOpTimeSeries, self.locationalEligibility)
(
self.aggregatedOpexPerChargeOpTimeSeries,
self.processedOpexPerChargeOpTimeSeries,
) = (None, None)
utils.isPositiveNumber(stateOfChargeTsaWeight), utils.isPositiveNumber(
opexChargeOpTsaWeight)
self.stateOfChargeTsaWeight, self.opexChargeOpTsaWeight = (
stateOfChargeTsaWeight,
opexChargeOpTsaWeight,
)
# Set locational eligibility
timeSeriesData = None
tsNb = sum([
0 if data is None else 1 for data in [
self.chargeOpRateMax,
self.chargeOpRateFix,
self.dischargeOpRateMax,
self.dischargeOpRateFix,
stateOfChargeOpRateMax,
stateOfChargeOpRateFix,
]
])
if tsNb > 0:
timeSeriesData = sum([
data for data in [
self.chargeOpRateMax,
self.chargeOpRateFix,
self.dischargeOpRateMax,
self.dischargeOpRateFix,
stateOfChargeOpRateMax,
stateOfChargeOpRateFix,
] if data is not None
])
self.locationalEligibility = utils.setLocationalEligibility(
esM,
self.locationalEligibility,
self.capacityMax,
self.capacityFix,
self.isBuiltFix,
self.hasCapacityVariable,
timeSeriesData,
)
def __init__(self,
esM,
name,
commodity,
losses=0,
distances=None,
hasCapacityVariable=True,
capacityVariableDomain='continuous',
capacityPerPlantUnit=1,
hasIsBuiltBinaryVariable=False,
bigM=None,
operationRateMax=None,
operationRateFix=None,
tsaWeight=1,
locationalEligibility=None,
capacityMin=None,
capacityMax=None,
sharedPotentialID=None,
capacityFix=None,
isBuiltFix=None,
investPerCapacity=0,
investIfBuilt=0,
opexPerOperation=0,
opexPerCapacity=0,
opexIfBuilt=0,
interestRate=0.08,
economicLifetime=10):
# TODO add unit checks
# Set general component data
utils.checkCommodities(esM, {commodity})
self._name, self._commodity = name, commodity
self._distances = utils.checkAndSetDistances(esM, distances)
self._losses = utils.checkAndSetTransmissionLosses(
esM, losses, distances)
# Set design variable modeling parameters
utils.checkDesignVariableModelingParameters(capacityVariableDomain,
hasCapacityVariable,
hasIsBuiltBinaryVariable,
bigM)
self._hasCapacityVariable = hasCapacityVariable
self._capacityVariableDomain = capacityVariableDomain
self._capacityPerPlantUnit = capacityPerPlantUnit
self._hasIsBuiltBinaryVariable = hasIsBuiltBinaryVariable
self._bigM = bigM
# Set economic data
self._investPerCapacity = utils.checkAndSetCostParameter(
esM, name, investPerCapacity, '2dim')
self._investIfBuilt = utils.checkAndSetCostParameter(
esM, name, investIfBuilt, '2dim')
self._opexPerOperation = utils.checkAndSetCostParameter(
esM, name, opexPerOperation, '2dim')
self._opexPerCapacity = utils.checkAndSetCostParameter(
esM, name, opexPerCapacity, '2dim')
self._opexIfBuilt = utils.checkAndSetCostParameter(
esM, name, opexIfBuilt, '2dim')
self._interestRate = utils.checkAndSetCostParameter(
esM, name, interestRate, '2dim')
self._economicLifetime = utils.checkAndSetCostParameter(
esM, name, economicLifetime, '2dim')
self._CCF = self.getCapitalChargeFactor()
# Set location-specific operation parameters
if operationRateMax is not None and operationRateFix is not None:
operationRateMax = None
warnings.warn(
'If operationRateFix is specified, the operationRateMax parameter is not required.\n'
+ 'The operationRateMax time series was set to None.')
utils.checkOperationTimeSeriesInputParameters(esM, operationRateMax,
locationalEligibility,
'2dim')
utils.checkOperationTimeSeriesInputParameters(esM, operationRateFix,
locationalEligibility,
'2dim')
self._fullOperationRateMax = utils.setFormattedTimeSeries(
operationRateMax)
self._aggregatedOperationRateMax = None
self._operationRateMax = utils.setFormattedTimeSeries(operationRateMax)
self._fullOperationRateFix = utils.setFormattedTimeSeries(
operationRateFix)
self._aggregatedOperationRateFix = None
self._operationRateFix = utils.setFormattedTimeSeries(operationRateFix)
self._tsaWeight = tsaWeight
# Set location-specific design parameters
self._sharedPotentialID = sharedPotentialID
utils.checkLocationSpecficDesignInputParams(
esM, hasCapacityVariable, hasIsBuiltBinaryVariable, capacityMin,
capacityMax, capacityFix, locationalEligibility, isBuiltFix,
sharedPotentialID, '2dim')
self._capacityMin, self._capacityMax, self._capacityFix = capacityMin, capacityMax, capacityFix
self._isBuiltFix = isBuiltFix
# Set locational eligibility
operationTimeSeries = operationRateFix if operationRateFix is not None else operationRateMax
self._locationalEligibility = utils.setLocationalEligibility(
esM, locationalEligibility, capacityMax, capacityFix, isBuiltFix,
hasCapacityVariable, operationTimeSeries, '2dim')
# Variables at optimum (set after optimization)
self._capacityVariablesOptimum = None
self._isBuiltVariablesOptimum = None
self._operationVariablesOptimum = None
def __init__(
self,
esM,
name,
commodity,
losses=0,
distances=None,
hasCapacityVariable=True,
capacityVariableDomain="continuous",
capacityPerPlantUnit=1,
hasIsBuiltBinaryVariable=False,
bigM=None,
operationRateMax=None,
operationRateFix=None,
tsaWeight=1,
locationalEligibility=None,
capacityMin=None,
capacityMax=None,
partLoadMin=None,
sharedPotentialID=None,
linkedQuantityID=None,
capacityFix=None,
isBuiltFix=None,
investPerCapacity=0,
investIfBuilt=0,
opexPerOperation=0,
opexPerCapacity=0,
opexIfBuilt=0,
QPcostScale=0,
interestRate=0.08,
economicLifetime=10,
technicalLifetime=None,
balanceLimitID=None,
):
"""
Constructor for creating an Transmission class instance.
The Transmission component specific input arguments are described below. The general component
input arguments are described in the Component class.
**Required arguments:**
:param commodity: to the component related commodity.
:type commodity: string
**Default arguments:**
:param losses: relative losses per lengthUnit (lengthUnit as specified in the energy system model) in
percentage of the commodity flow. This loss factor can capture simple linear losses
.. math::
trans_{in, ij} = (1 - \\text{losses} \\cdot \\text{distances}) \\cdot trans_{out, ij}
(with trans being the commodity flow at a certain point in
time and i and j being locations in the energy system). The losses can either be given as a float or a
Pandas DataFrame with location specific values.
|br| * the default value is 0
:type losses: positive float (0 <= float <= 1) or Pandas DataFrame with positive values
(0 <= float <= 1). The row and column indices of the DataFrame have to equal the in the energy
system model specified locations.
:param distances: distances between locations given in the lengthUnit (lengthUnit as specified in
the energy system model).
|br| * the default value is None
:type distances: positive float (>= 0) or Pandas DataFrame with positive values (>= 0). The row and
column indices of the DataFrame have to equal the in the energy system model specified locations.
:param operationRateMax: if specified, indicates a maximum operation rate for all possible connections
(both directions) of the transmission component at each time step by a positive float. If
hasCapacityVariable is set to True, the values are given relative to the installed capacities (i.e.
a value of 1 indicates a utilization of 100% of the capacity). If hasCapacityVariable
is set to False, the values are given as absolute values in form of the commodityUnit,
referring to the transmitted commodity (before considering losses) during one time step.
|br| * the default value is None
:type operationRateMax: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices are combinations
of locations (as defined in the energy system model), separated by a underscore (e.g.
"location1_location2"). The first location indicates where the commodity is coming from. The second
location indicates where the commodity is going too. If a flow is specified from location i to
location j, it also has to be specified from j to i.
:param operationRateFix: if specified, indicates a fixed operation rate for all possible connections
(both directions) of the transmission component at each time step by a positive float. If
hasCapacityVariable is set to True, the values are given relative to the installed capacities (i.e.
a value of 1 indicates a utilization of 100% of the capacity). If hasCapacityVariable
is set to False, the values are given as absolute values in form of the commodityUnit,
referring to the transmitted commodity (before considering losses) during one time step.
|br| * the default value is None
:type operationRateFix: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices are combinations
of locations (as defined in the energy system model), separated by a underscore (e.g.
"location1_location2"). The first location indicates where the commodity is coming from. The second
one location indicates where the commodity is going too. If a flow is specified from location i to
location j, it also has to be specified from j to i.
:param tsaWeight: weight with which the time series of the component should be considered when applying
time series aggregation.
|br| * the default value is 1
:type tsaWeight: positive (>= 0) float
:param opexPerOperation: describes the cost for one unit of the operation.
The cost which is directly proportional to the operation of the component is obtained by multiplying
the opexPerOperation parameter with the annual sum of the operational time series of the components.
The opexPerOperation can either be given as a float or a Pandas DataFrame with location specific values.
The cost unit in which the parameter is given has to match the one specified in the energy
system model (e.g. Euro, Dollar, 1e6 Euro). The value has to match the unit costUnit/operationUnit
(e.g. Euro/kWh, Dollar/kWh).
|br| * the default value is 0
:type opexPerOperation: positive (>=0) float or Pandas DataFrame with positive (>=0) values.
The row and column indices of the DataFrame have to equal the in the energy system model
specified locations.
:param balanceLimitID: ID for the respective balance limit (out of the balance limits introduced in the esM).
Should be specified if the respective component of the TransmissionModel is supposed to be included in
the balance analysis. If the commodity is transported out of the region, it is counted as a negative, if
it is imported into the region it is considered positive.
|br| * the default value is None
:type balanceLimitID: string
"""
# TODO add unit checks
# Preprocess two-dimensional data
self.locationalEligibility = utils.preprocess2dimData(
locationalEligibility)
self.capacityMax = utils.preprocess2dimData(
capacityMax, locationalEligibility=locationalEligibility)
self.capacityFix = utils.preprocess2dimData(
capacityFix, locationalEligibility=locationalEligibility)
self.isBuiltFix = utils.preprocess2dimData(
isBuiltFix, locationalEligibility=locationalEligibility)
# Set locational eligibility
operationTimeSeries = (operationRateFix if operationRateFix is not None
else operationRateMax)
self.locationalEligibility = utils.setLocationalEligibility(
esM,
self.locationalEligibility,
self.capacityMax,
self.capacityFix,
self.isBuiltFix,
hasCapacityVariable,
operationTimeSeries,
"2dim",
)
self._mapC, self._mapL, self._mapI = {}, {}, {}
for loc1 in esM.locations:
for loc2 in esM.locations:
if loc1 + "_" + loc2 in self.locationalEligibility.index:
if self.locationalEligibility[loc1 + "_" + loc2] == 0:
self.locationalEligibility.drop(labels=loc1 + "_" +
loc2,
inplace=True)
self._mapC.update({loc1 + "_" + loc2: (loc1, loc2)})
self._mapL.setdefault(loc1,
{}).update({loc2: loc1 + "_" + loc2})
self._mapI.update({loc1 + "_" + loc2: loc2 + "_" + loc1})
self.capacityMax = utils.preprocess2dimData(
capacityMax,
self._mapC,
locationalEligibility=self.locationalEligibility)
self.capacityFix = utils.preprocess2dimData(
capacityFix,
self._mapC,
locationalEligibility=self.locationalEligibility)
self.capacityMin = utils.preprocess2dimData(
capacityMin,
self._mapC,
locationalEligibility=self.locationalEligibility)
self.investPerCapacity = utils.preprocess2dimData(
investPerCapacity, self._mapC)
self.investIfBuilt = utils.preprocess2dimData(investIfBuilt,
self._mapC)
self.isBuiltFix = utils.preprocess2dimData(
isBuiltFix,
self._mapC,
locationalEligibility=self.locationalEligibility)
self.opexPerCapacity = utils.preprocess2dimData(
opexPerCapacity, self._mapC)
self.opexIfBuilt = utils.preprocess2dimData(opexIfBuilt, self._mapC)
self.interestRate = utils.preprocess2dimData(interestRate, self._mapC)
self.economicLifetime = utils.preprocess2dimData(
economicLifetime, self._mapC)
self.technicalLifetime = utils.preprocess2dimData(
technicalLifetime, self._mapC)
self.balanceLimitID = balanceLimitID
Component.__init__(
self,
esM,
name,
dimension="2dim",
hasCapacityVariable=hasCapacityVariable,
capacityVariableDomain=capacityVariableDomain,
capacityPerPlantUnit=capacityPerPlantUnit,
hasIsBuiltBinaryVariable=hasIsBuiltBinaryVariable,
bigM=bigM,
locationalEligibility=self.locationalEligibility,
capacityMin=self.capacityMin,
capacityMax=self.capacityMax,
partLoadMin=partLoadMin,
sharedPotentialID=sharedPotentialID,
linkedQuantityID=linkedQuantityID,
capacityFix=self.capacityFix,
isBuiltFix=self.isBuiltFix,
investPerCapacity=self.investPerCapacity,
investIfBuilt=self.investIfBuilt,
opexPerCapacity=self.opexPerCapacity,
opexIfBuilt=self.opexIfBuilt,
interestRate=self.interestRate,
QPcostScale=QPcostScale,
economicLifetime=self.economicLifetime,
technicalLifetime=self.technicalLifetime,
)
# Set general component data
utils.checkCommodities(esM, {commodity})
self.commodity, self.commodityUnit = (
commodity,
esM.commodityUnitsDict[commodity],
)
self.distances = utils.preprocess2dimData(
distances,
self._mapC,
locationalEligibility=self.locationalEligibility)
self.losses = utils.preprocess2dimData(losses, self._mapC)
self.distances = utils.checkAndSetDistances(self.distances,
self.locationalEligibility,
esM)
self.losses = utils.checkAndSetTransmissionLosses(
self.losses, self.distances, self.locationalEligibility)
self.modelingClass = TransmissionModel
# Set distance related costs data
self.processedInvestPerCapacity = self.investPerCapacity * self.distances * 0.5
self.processedInvestIfBuilt = self.investIfBuilt * self.distances * 0.5
self.processedOpexPerCapacity = self.opexPerCapacity * self.distances * 0.5
self.processedOpexIfBuilt = self.opexIfBuilt * self.distances * 0.5
# Set additional economic data
self.opexPerOperation = utils.preprocess2dimData(
opexPerOperation, self._mapC)
self.opexPerOperation = utils.checkAndSetCostParameter(
esM, name, self.opexPerOperation, "2dim",
self.locationalEligibility)
self.operationRateMax = operationRateMax
self.operationRateFix = operationRateFix
self.fullOperationRateMax = utils.checkAndSetTimeSeries(
esM, name, operationRateMax, self.locationalEligibility,
self.dimension)
self.aggregatedOperationRateMax, self.processedOperationRateMax = None, None
self.fullOperationRateFix = utils.checkAndSetTimeSeries(
esM, name, operationRateFix, self.locationalEligibility,
self.dimension)
self.aggregatedOperationRateFix, self.processedOperationRateFix = None, None
# Set location-specific operation parameters
if (self.fullOperationRateMax is not None
and self.fullOperationRateFix is not None):
self.fullOperationRateMax = None
if esM.verbose < 2:
warnings.warn(
"If operationRateFix is specified, the operationRateMax parameter is not required.\n"
+ "The operationRateMax time series was set to None.")
if self.partLoadMin is not None:
if self.fullOperationRateMax is not None:
if (((self.fullOperationRateMax > 0)
& (self.fullOperationRateMax < self.partLoadMin)
).any().any()):
raise ValueError(
'"fullOperationRateMax" needs to be higher than "partLoadMin" or 0 for component '
+ name)
if self.fullOperationRateFix is not None:
if (((self.fullOperationRateFix > 0)
& (self.fullOperationRateFix < self.partLoadMin)
).any().any()):
raise ValueError(
'"fullOperationRateFix" needs to be higher than "partLoadMin" or 0 for component '
+ name)
utils.isPositiveNumber(tsaWeight)
self.tsaWeight = tsaWeight
def __init__(self,
esM,
name,
commodity,
chargeRate=1,
dischargeRate=1,
chargeEfficiency=1,
dischargeEfficiency=1,
selfDischarge=0,
cyclicLifetime=None,
stateOfChargeMin=0,
stateOfChargeMax=1,
hasCapacityVariable=True,
capacityVariableDomain='continuous',
capacityPerPlantUnit=1,
hasIsBuiltBinaryVariable=False,
bigM=None,
doPreciseTsaModeling=False,
chargeOpRateMax=None,
chargeOpRateFix=None,
chargeTsaWeight=1,
dischargeOpRateMax=None,
dischargeOpRateFix=None,
dischargeTsaWeight=1,
stateOfChargeOpRateMax=None,
stateOfChargeOpRateFix=None,
stateOfChargeTsaWeight=1,
isPeriodicalStorage=False,
locationalEligibility=None,
capacityMin=None,
capacityMax=None,
sharedPotentialID=None,
capacityFix=None,
isBuiltFix=None,
investPerCapacity=0,
investIfBuilt=0,
opexPerChargeOperation=0,
opexPerDischargeOperation=0,
opexPerCapacity=0,
opexIfBuilt=0,
interestRate=0.08,
economicLifetime=10):
"""
Constructor for creating an Storage class instance.
The Storage component specific input arguments are described below. The general component
input arguments are described in the Component class.
**Default arguments:**
:param stateOfChargeOpRateMax: if specified indicates a maximum state of charge for each location and
each time step by a positive float. If hasCapacityVariable is set to True, the values are given
relative to the installed capacities (i.e. in that case a value of 1 indicates a utilization of
100% of the capacity). If hasCapacityVariable is set to False, the values are given as absolute
values in form of the commodityUnit, referring to the commodity stored in the component at the
beginning of one time step.
|br| * the default value is None
:type stateOfChargeOpRateMax: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices have to match the
in the energy system model specified locations.
:param stateOfChargeOpRateFix: if specified indicates a fixed state of charge for each location and
each time step by a positive float. If hasCapacityVariable is set to True, the values are given
relative to the installed capacities (i.e. in that case a value of 1 indicates a utilization of
100% of the capacity). If hasCapacityVariable is set to False, the values are given as absolute
values in form of the commodityUnit, referring to the commodity stored in the component at the
beginning of one time step.
|br| * the default value is None
:type stateOfChargeOpRateFix: None or Pandas DataFrame with positive (>= 0) entries. The row indices have
to match the in the energy system model specified time steps. The column indices have to match the
in the energy system model specified locations.
:param stateOfChargeTsaWeight: weight with which the stateOfChargeOpRate (max/fix) time series of the
component should be considered when applying time series aggregation.
|br| * the default value is 1
:type stateOfChargeTsaWeight: positive (>= 0) float
"""
Storage.__init__(
self, esM, name, commodity, chargeRate, dischargeRate,
chargeEfficiency, dischargeEfficiency, selfDischarge,
cyclicLifetime, stateOfChargeMin, stateOfChargeMax,
hasCapacityVariable, capacityVariableDomain, capacityPerPlantUnit,
hasIsBuiltBinaryVariable, bigM, doPreciseTsaModeling,
chargeOpRateMax, chargeOpRateFix, chargeTsaWeight,
dischargeOpRateMax, dischargeOpRateFix, dischargeTsaWeight,
isPeriodicalStorage, locationalEligibility, capacityMin,
capacityMax, sharedPotentialID, capacityFix, isBuiltFix,
investPerCapacity, investIfBuilt, opexPerChargeOperation,
opexPerDischargeOperation, opexPerCapacity, opexIfBuilt,
interestRate, economicLifetime)
# Set location-specific operation parameters (Charging rate, discharging rate, state of charge rate)
# and time series aggregation weighting factor
# The i-th state of charge (SOC) refers to the SOC before the i-th time step
if stateOfChargeOpRateMax is not None and stateOfChargeOpRateFix is not None:
stateOfChargeOpRateMax = None
if esM.verbose < 2:
warnings.warn(
'If stateOfChargeOpRateFix is specified, the stateOfChargeOpRateMax parameter is not +'
'required.\nThe stateOfChargeOpRateMax time series was set to None.'
)
if (stateOfChargeOpRateMax is not None or stateOfChargeOpRateFix
is not None) and not doPreciseTsaModeling:
self.doPreciseTsaModeling = True
if esM.verbose < 2:
warnings.warn(
'Warning only relevant when time series aggregation is used in optimization:\n'
+
'If stateOfChargeOpRateFix or the stateOfChargeOpRateMax parameter are specified,\n'
+ 'the modeling is set to precise.')
if stateOfChargeOpRateMax is not None:
if esM.verbose < 2:
warnings.warn(
'Warning only relevant when time series aggregation is used in optimization:\n'
+
'Setting the stateOfChargeOpRateMax parameter might lead to unwanted modeling behavior\n'
+ 'and should be handled with caution.')
if stateOfChargeOpRateFix is not None and not isPeriodicalStorage:
self.isPeriodicalStorage = True
if esM.verbose < 2:
warnings.warn(
'Warning only relevant when time series aggregation is used in optimization:\n'
+
'If the stateOfChargeOpRateFix parameter is specified, the storage\n'
+ 'is set to isPeriodicalStorage).')
utils.checkOperationTimeSeriesInputParameters(esM,
stateOfChargeOpRateMax,
locationalEligibility)
utils.checkOperationTimeSeriesInputParameters(esM,
stateOfChargeOpRateFix,
locationalEligibility)
self.fullStateOfChargeOpRateMax = utils.setFormattedTimeSeries(
stateOfChargeOpRateMax)
self.aggregatedStateOfChargeOpRateMax = None
self.stateOfChargeOpRateMax = None
self.fullStateOfChargeOpRateFix = utils.setFormattedTimeSeries(
stateOfChargeOpRateFix)
self.aggregatedStateOfChargeOpRateFix = None
self.stateOfChargeOpRateFix = None
utils.isPositiveNumber(stateOfChargeTsaWeight)
self.stateOfChargeTsaWeight = stateOfChargeTsaWeight
# Set locational eligibility
timeSeriesData = None
tsNb = sum([
0 if data is None else 1 for data in [
chargeOpRateMax, chargeOpRateFix, dischargeOpRateMax,
dischargeOpRateFix, stateOfChargeOpRateMax,
stateOfChargeOpRateFix
]
])
if tsNb > 0:
timeSeriesData = sum([
data for data in [
chargeOpRateMax, chargeOpRateFix, dischargeOpRateMax,
dischargeOpRateFix, stateOfChargeOpRateMax,
stateOfChargeOpRateFix
] if data is not None
])
self.locationalEligibility = \
utils.setLocationalEligibility(esM, self.locationalEligibility, self.capacityMax, self.capacityFix,
self.isBuiltFix, self.hasCapacityVariable, timeSeriesData)
