Power Demand-Supply Adjustment via Negawatt Trading Based on Regret Matching

This study deals with power demand-supply management based on negawatt trading. The aim of this study is to minimize the social cost of negawatt trading and maintain a demand-supply balance. Power consumers and independent system operators participate in the electricity market and each consumer acts based on regret matching, which is one of the learning algorithms. Furthermore, we consider strategy-proofness and individual rationality using VCG mechanism design. In this study, we propose a novel negawatt trading procedure based on regret matching and VCG mechanism design. Finally, the simulation results confirm the effectiveness of the proposed algorithm.