Distributed demand response algorithms against semi-honest adversaries

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    10 Scopus citations

    Abstract

    This paper investigates two problems for demand response: demand allocation market and demand shedding market. By utilizing reinforcement learning, stochastic approximation and secure multi-party computation, we propose two distributed algorithms to solve the induced games respectively. The proposed algorithms are able to protect the privacy of the market participants, including the system operator and end users. The algorithm convergence is formally ensured and the algorithm performance is verified via numerical simulations.

    Original languageEnglish (US)
    Title of host publication2014 IEEE PES General Meeting / Conference and Exposition
    PublisherIEEE Computer Society
    EditionOctober
    ISBN (Electronic)9781479964154
    DOIs
    StatePublished - Oct 29 2014
    Event2014 IEEE Power and Energy Society General Meeting - National Harbor, United States
    Duration: Jul 27 2014Jul 31 2014

    Publication series

    NameIEEE Power and Energy Society General Meeting
    NumberOctober
    Volume2014-October
    ISSN (Print)1944-9925
    ISSN (Electronic)1944-9933

    Other

    Other2014 IEEE Power and Energy Society General Meeting
    Country/TerritoryUnited States
    CityNational Harbor
    Period7/27/147/31/14

    All Science Journal Classification (ASJC) codes

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

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