TALK    A Dirichlet Process Mixture Model for Clustering of Household Electricity Load Profiles

Date released: July 30, 2013

  •  TALK    A Dirichlet Process Mixture Model for Clustering of Household Electricity Load Profiles
  • Date & Time:

    Tuesday, July 30, 2013; 12:00 PM

  • Abstract:

    We show that real electricity-use patterns can be distinguished using a Bayesian nonparametric model based on the Dirichlet Process Mixture Model. By modelling the load profiles as discrete counters we make use of the Dirichlet-Multinomial distribution. Clusters are computed with the Chinese Restaurant Process method and posterior probabilities distributions estimated with a Gibbs sampling algorithm.

  • Speaker:

    Ramon Granell
    Oxford University

  • MERL Host:

    Daniel N. Nikovski

  • Research Area:

    Data Analytics