Dynamic Risk Management for Demand Response in Multi-Utility Smart Grids

This research work is motivated by the need for effective demand response management (DRM) in smart grid systems. DRM is critical in optimizing the energy load by adjusting the energy prices and shifting high electricity demand to off-peak periods. This paper introduces a novel DRM model in a multi-user multi-utility company environment, considering the risk and uncertainty stemming from potential excessive energy demands, where each utility company is treated as a Common Pool of Resources (CPR). The risk-aware behavior of the consumers is captured using the Prospect Theory principles. Specifically, to model the interactions, we formulate a multi-leader multi-follower Stackelberg game involving the utility companies as leaders and the consumers as followers. The goal is to determine the optimal energy prices for the utility companies and the optimal amount of energy that each consumer purchases from these companies, considering their distributed decision-making process and exploring the non-cooperative Game Theory. The proposed DRM framework is assessed through numerical results, demonstrating its operational and performance efficiency. The results highlight the key benefits and tradeoffs of our model in comparison to alternative DRM strategies, emphasizing the significance of the presented approach in managing demand response effectively.