Publication | Closed Access
Generation of flexible domestic load profiles to evaluate Demand Side Management approaches
65
Citations
13
References
2016
Year
Unknown Venue
EngineeringPower Grid OperationEnergy EfficiencyLoad ProfilesLoad ControlEnergy Management SystemOperations ResearchLogisticsSystems EngineeringLoad ManagementQuantitative ManagementEnergy Demand ManagementDemand ManagementElectrical EngineeringDemand ForecastingComputer EngineeringDsm MethodologiesLoad Profile GeneratorDemand-side ManagementSmart GridEnergy ManagementBusinessDemand Response
Demand Side Management approaches have been developed to avoid costly grid upgrades, but their evaluation is often limited to use‑case specific examples, hindering comparison. This paper introduces an open‑source load‑profile generator to evaluate and compare DSM approaches. The generator produces minute‑interval load and flexibility data for active and reactive power of controllable domestic devices using a simple behavioural simulation and device measurements. Field tests confirm that the generated profiles match measured household and neighbourhood data, reproducing dynamics such as unbalanced loading and rapid consumption fluctuations.
Various Demand Side Management (DSM) approaches have been developed the last couple of years to avoid costly grid upgrades. However, evaluation of these DSM methodologies is usually restricted to a use-case specific example, making comparison between different DSM approaches hard. This paper presents a novel, open source, load profile generator to evaluate and compare DSM approaches. In addition to static load profiles for both active and reactive power, it also provides flexibility information for various classes of controllable domestic devices. Load profiles and flexibility information are generated using a simple behavioural simulation. The output data uses 1 minute intervals and incorporates device measurements. The generated profiles are in sound with the measurement data obtained in a field test on both the household level and aggregated neighbourhood level. The same dynamics, such as unbalanced loading and rapid power consumption fluctuations, are observed in the generated model.
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