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Publication

Genetic algorithm for demand response: a stackelberg game approach...

by Kadir Amasyali, Mohammed M Olama, Yang Chen
Publication Type
Conference Paper
Book Title
Proceedings of the 2020 Spring Simulation Conference
Publication Date
Page Number
49
Conference Name
The 2020 Spring Simulation Conference (SpringSim’20)
Conference Location
Fairfax, Virginia, United States of America
Conference Sponsor
The Society for Modeling and Simulation International (SCS)
Conference Date
-

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.