Distributed demand response algorithms against semi-honest adversaries

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

12 Scopus citations


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
ISBN (Electronic)9781479964154
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
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933


Other2014 IEEE Power and Energy Society General Meeting
Country/TerritoryUnited States
CityNational Harbor

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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