Package agents.forecast

Class PowerForecastError

java.lang.Object

agents.forecast.PowerForecastError

public class PowerForecastError
extends Object

Calculates power values with errors following a normal distribution for power forecasting

Author:

Johannes Kochems, Christoph Schimeczek

Field Summary

Fields

Modifier and Type	Field	Description
static de.dlr.gitlab.fame.agent.input.Tree	parameters	Specific inputs to parameterise PowerForecastError modelling

Constructor Summary

Constructors

Constructor	Description
PowerForecastError(de.dlr.gitlab.fame.agent.input.ParameterData input, Random random)	Creates a PowerForecastError

Method Summary

Modifier and Type	Method	Description
double	calcPowerWithError(double powerWithoutError)	Calculates a power forecast with errors following a normal distribution

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

parameters

public static final de.dlr.gitlab.fame.agent.input.Tree parameters

Specific inputs to parameterise PowerForecastError modelling

Constructor Detail

PowerForecastError

public PowerForecastError(de.dlr.gitlab.fame.agent.input.ParameterData input,
                          Random random)
                   throws de.dlr.gitlab.fame.agent.input.ParameterData.MissingDataException

Creates a PowerForecastError

Parameters:

input - parameter group according to parameters

random - random number generator - use FAME's RNG creation function to ensure reproducibility on identical seeds

Throws:

de.dlr.gitlab.fame.agent.input.ParameterData.MissingDataException - if any required data is not provided

Method Detail

calcPowerWithError

public double calcPowerWithError(double powerWithoutError)

Calculates a power forecast with errors following a normal distribution

Parameters:

powerWithoutError - perfect foresight power forecast

Returns:

given power multiplied with a randomly generated forecast error factor