Efficient real-time residential energy management through MILP based rolling horizon optimization

Haiming Wang, Ke Meng, Zhao Yang Dong, Zhao Xu, Fengji Luo, Kit Po Wong

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

23 Citations (Scopus)


In this paper, a Mixed Integer Linear Programming (MILP) based rolling optimization approach under real time pricing (RTP) policy is introduced to efficiently manage energy consumption of a smart home equipped with a Battery Energy Storage System (BESS) and a solar PV system. Models of distributed energy resources (DERs) in a smart house are developed and accordingly optimal management of total energy consumption is formulated as a MILP problem, which is then solved by the MOSEK software platform. And a rolling optimization scheduling framework based on MILP is proposed to dispatch DERs within a smart home to minimize the expenditure under RTP policy. Case studies are conducted to validate the performance of the algorithm. It is observed that proposed algorithm could benefit both smart house owners and network operators technically and economically in the context of smart grid.
Original languageEnglish
Title of host publication2015 IEEE Power and Energy Society General Meeting, PESGM 2015
PublisherIEEE Computer Society
ISBN (Electronic)9781467380409
Publication statusPublished - 30 Sep 2015
EventIEEE Power and Energy Society General Meeting, PESGM 2015 - Denver, United States
Duration: 26 Jul 201530 Jul 2015


ConferenceIEEE Power and Energy Society General Meeting, PESGM 2015
Country/TerritoryUnited States


  • Demand Response
  • Mixed Integer Linear Programming
  • Rolling Optimization
  • Smart Home Energy Management System

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

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