Multi-layer Agent-Based Decision Making Model with Incomplete Information Game Theory to Study the Behavior of Market Participants for Sustainability

This paper presents a new stochastic multi-layer agent-based decision making model to study the behavior of market participants in the future smart grid. In the agent-based model proposed, wholesale market players are modeled in the first layer. The players include renewable/sustainable power producers, optimizing the bidding/offering strategies to participate in the electricity markets. In the second layer, responsive customers include electric vehicle owners and consumers who participate in demand response programs, being modeled as independent agents. The objective of the responsive customers is to increase their benefit while retaining welfare. The interaction between market players in day-ahead and real-time markets is modeled using an incomplete information game theory algorithm. According to the high uncertainty of resources and customers´ behavior, the model is developed using a stochastic framework. A case study containing wind power producers, aggregators and retailers providing demand response is considered to confirm the usefulness of the proposed multi-layer model.