Genetic algorithm for demand response: A stackelberg game approach

Kadir Amasyali, Mohammed M. Olama, Yang Chen

Research output: Contribution to journalConference articlepeer-review

Abstract

Demand response (DR) has gained a significant recent interest due to its potential for mitigating many power system problems. Game theory is a very effective tool to be utilized in DR management. In this paper, the DR between a distribution system operator (DSO) and load aggregators (LAs) is designed as a Stackelberg game, where the DSO acts as the leader and LAs are regarded as the followers. Due to the limitations of the centralized solution approaches, a genetic algorithm-based decentralized approach is proposed. To demonstrate the proposed approach, a case study concerning a day-ahead optimization for a real-time pricing market with a single DSO and three LAs is designed and optimized. The proposed approach is able to shift the demand peaks and prove that it has a great potential to be used for the Stackelberg game between a DSO and multiple LAs to fully exploit the potential of DR.

Original languageEnglish
Pages (from-to)560-571
Number of pages12
JournalSimulation Series
Volume52
Issue number1
StatePublished - 2020
Event2020 Spring Simulation Multiconference, SpringSim 2020 - Virtual, Online
Duration: May 18 2020May 21 2020

Funding

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Keywords

  • Demand response
  • Genetic algorithms
  • Smart grid
  • Stackelberg game

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