Modeling electricity load curves with hidden Markov models for demand-side management status estimation

The development of the smart grid will lead to increased possibilities to improve energy efficiency via demand-side management (DSM) and ultimately contribute to a more sustainable and secure energy system. The smart grid will offer great opportunities for developing methods for automatic analyses of various states in the energy system. This paper proposes a method that aims to classify load curves and estimate current power reduction capacity from DSM. The method is based on the hidden Markov model where the hidden states represent customers' demand behaviors in an aggregated load curve. The method is tested on 3 aggregated load curves, based on measured data from 36 Swedish companies. Results show that the method can recognize when DSM has been utilized as well when DSM has not been utilized. Results also show that the energy system becomes more stable, from a system dynamical point of view, when DSM is utilized.