Hierarchical Game Approach for Optimization of Regional Integrated Energy System Clusters Considering Bounded Rationality

Abstract

Regional integrated energy system (RIES) cluster, i.e., multi-source integration and multi-region coordination, is an effective approach for increasing energy utilization efficiency. The hierarchical architecture and limited information sharing of RIES cluster make it difficult for traditional game theory to accurately describe their game behavior. Thus, a hierarchical game approach considering bounded rationality is proposed in this paper to balance the interests of optimizing RIES cluster under privacy protection. A Stackelberg game with the cluster operator (CO) as the leader and multiple RIES as followers is developed to simultaneously optimize leader benefit and RIES utilization efficiency. Concurrently, a slight altruistic function is introduced to simulate the game behavior of each RIES agent on whether to cooperate or not. By introducing an evolutionary game based on bounded rationality in the lower layer, the flaw of the assumption that participants are completely rational can be avoided. Specially, for autonomous optimal dispatching, each RIES is treated as a prosumer, flexibly switching its market participation role to achieve cluster coordination optimization. Case studies on a RIES cluster verify effectiveness of the proposed approach.

Keywords

• Bounded rationality
• coordinated optimization
• evolutionary game
• regional integrated energy system
• stackelberg game