Real-time power balancing via decentralized coordinated home energy scheduling

Tsung Hui Chang, Mahnoosh Alizadeh, Anna Scaglione

Research output: Contribution to journalArticlepeer-review

112 Scopus citations

Abstract

It is anticipated that an uncoordinated operation of individual home energy management (HEM) systems in a neighborhood would have a rebound effect on the aggregate demand profile. To address this issue, this paper proposes a coordinated home energy management (CoHEM) architecture in which distributed HEM units collaborate with each other in order to keep the demand and supply balanced in their neighborhood. Assuming the energy requests by customers are random in time, we formulate the proposed CoHEM design as a multi-stage stochastic optimization problem. We propose novel models to describe the deferrable appliance load [e.g., plug-in (hybrid) electric vehicles (PHEV)], and apply approximation and decomposition techniques to handle the considered design problem in a decentralized fashion. The developed decentralized CoHEM algorithm allow the customers to locally compute their scheduling solutions using domestic user information and with message exchange between their neighbors only. Extensive simulation results demonstrate that the proposed CoHEM architecture can effectively improve real-time power balancing. Extensions to joint power procurement and real-time CoHEM scheduling are also presented.

Original languageEnglish (US)
Article number6575162
Pages (from-to)1490-1504
Number of pages15
JournalIEEE Transactions on Smart Grid
Volume4
Issue number3
DOIs
StatePublished - Aug 12 2013
Externally publishedYes

Keywords

  • Deferrable loads
  • Markov decision process
  • demand response
  • demand side management
  • distributed optimization
  • home energy management
  • power balancing

ASJC Scopus subject areas

  • Computer Science(all)

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