Hierarchical Demand Response for Peak Minimization Using Dantzig–Wolfe Decomposition

Paul McNamara, Sean McLoone

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


Demand Response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using acentralised agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustnessto communication failures. Thus it is desirable to use a scalabledecentralised algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for Peak Minimisation(PM) based on Dantzig-Wolfe Decomposition (DWD). Inaddition, a Time Weighted Maximisation option is included in thecost function which improves the Quality of Service for devicesseeking to receive their desired energy sooner rather than later.The paper also demonstrates how the DWD algorithm can beimplemented more efficiently through the calculation of the upperand lower cost bounds after each DWD iteration.
Original languageEnglish
Article number7230291
Pages (from-to)2807 - 2815
Number of pages9
JournalIEEE Transactions on Smart Grid
Issue number6
Early online date31 Aug 2015
Publication statusPublished - Nov 2015


  • Dantzig-Wolfe decomposition (DWD)
  • demand response (DR)
  • demand side management (DSM)
  • hierarchical
  • peak minimization (PM)

ASJC Scopus subject areas

  • Computer Science(all)


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