Residential Electrical Load Model Based on Mixture Model Clustering and Markov Models
IEEE Transactions on Industrial InformaticsPublished 15 January 2013Open access
Wouter Labeeuw, Geert Deconinck
Citations135
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TL;DR
A top-down model of the residential electrical load, based on a dataset of over 1300 load profiles, is presented, and the inverse of the probability distribution of the electrical power is used to translate the resulting states into electrical power.
Abstract
Detailed large-scale simulations require a lot of data. Residential electrical load profiles are well protected by privacy laws. Representative residential electrical load generators get around the privacy problem and allow for Monte Carlo simulations. A top-down model of the residential electrical load, based on a dataset of over 1300 load profiles, is presented in this paper. The load profiles are clustered by a Mixed Model to group similar ones. Within the group, a behavior model is constructed with a Markov model. The states of the Markov models are based on the probability distribution of the electrical power. A second Markov model is created to randomize the behavior. A load profile is created by first performing a random-walking of the Markov models to get a sequence of states. The inverse of the probability distribution of the electrical power is used to translate the resulting states into electrical power.
Keywords
Engineering
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