A partially observable markov decision process approach to residential home energy management

Academic Article

Abstract

  • © 2016 IEEE. Real-time pricing (RTP) is a utility-offered dynamic pricing program to incentivize customers to make changes in their energy usage. A home energy management system (HEMS) automates the energy usage in a smart home in response to utility pricing signals. We present three new HEMS techniques-one myopic approach and two non-myopic partially observable Markov decision process (POMDP) approaches-for minimizing the household electricity bill in such a RTP market. In a simulation study, we compare the performance of the new HEMS methods with a mathematical lower bound and the status quo. We show that the non-myopic POMDP approach can provide a 10%-30% saving over the status quo.
  • Authors

    Published In

    Digital Object Identifier (doi)

    Pubmed Id

  • 11148487
  • Author List

  • Hansen TM; Chong EKP; Suryanarayanan S; Maciejewski AA; Siegel HJ
  • Start Page

  • 1271
  • End Page

  • 1281
  • Volume

  • 9
  • Issue

  • 2