Abstract
Increasing penetration of distributed energy resources, varying load demands and big data of smart meters require new load models to support power system studies. The big data of smart meters and non-linearities in the load demand require the smart meter data to be represented in an alternative way to use in stochastic simulations to enhance processing. This paper proposes a novel method for stochastic load modelling of smart meter data. The approach turns smart meter data to a manageable level by linearizing energy consumption patterns producing energy classifications. A case study, using real world smart meter data, simulated scenarios to prove the robustness and accuracy of the method. The accuracy of results validates the stability and robustness of the approach and model validation provided substantiation for application in probabilistic studies.
Published Version
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