Reverse auction-based demand response program: A truthful mutually beneficial mechanism

Atieh R. Khamesi, Simone Silvestri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Matching power demand during peak load hours is a well-known problem in power systems. In fact, the cost of producing electricity increases very rapidly when the demand is high, due to the need for starting backup generators and enhancing transmission system. Incentive-based Demand Response (DR) program is a new approach, enabled by recent advances in smart grid technologies, designed to deal with such problem. According to DR, the utility company can provide economical incentives to users in order to temporarily reduce their energy consumption during peak hours. It is, however, challenging to determine the procedure to distribute such incentives, as well as to ensure that users will be sufficiently engaged and satisfied to make the DR program effective. In this paper, we propose a reverse auction mechanism to enable an incentive-based DR program. We formulate the DR reverse auction as an integer linear programming (ILP) problem, which integrates a perceived-value utility, to model the user perception of electrical appliances, as well as the financial objectives of the utility company. We adopt a Vickrey-Clarke-Groves (VCG) based reverse auction mechanism to guarantee the truthfulness and individual rationality properties. Since the VCG auction requires to optimally solve the NP-Hard ILP problem, we propose a heuristic algorithm named Reverse Auction DemAnd Response (RADAR), and prove that RADAR preserves truthfulness. Extensive simulations using real power consumption data of several homes show that RADAR is effective in reducing demand peaks while outperforming previous solutions in terms of users' perceived utility.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 17th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2020
Pages427-436
Number of pages10
ISBN (Electronic)9781728198668
DOIs
StatePublished - Dec 2020
Event17th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2020 - Virtual, Delhi, India
Duration: Dec 10 2020Dec 13 2020

Publication series

NameProceedings - 2020 IEEE 17th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2020

Conference

Conference17th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2020
Country/TerritoryIndia
CityVirtual, Delhi
Period12/10/2012/13/20

Bibliographical note

Funding Information:
This work is supported by the National Institute for Food and Agriculture (NIFA) under the grant 2017-67008-26145, the NSF grant EPCN 1936131, and the NSF CAREER grant CPS-1943035.

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Incentive-based Demand Response
  • Individual Rationality
  • Perceivedvalue User Utility
  • Truthful Auction
  • VCG-based Reverse Auction

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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