A Multi-Criteria Evolutionary Game for Cyber-Physical Microgrids With Adaptive Resilience

Traditional optimization models and classical game theories face significant limitations when describing the interactive decision-making of multiple market agents in cyber-physical microgrid clusters under bounded rationality. To address this challenge, a collaborative optimization strategy for electricity, carbon, and hydrogen agents is proposed based on the evolutionary game to solve the bounded-rationality decision-making problems of multi-stakeholders within cyber-physical systems. Then, to break through the limitation of existing evolutionary game models that can only evolve with a single criterion, a novel multi-criteria repetitive evolutionary game model is developed, which can also reconcile the contradiction between the continuity need of system optimization and finite discrete strategy sets of the evolutionary game. Moreover, a multi-price-based demand response (DR) and an adaptive optimal load elasticity calculation method driven by benefits are proposed to further enhance the revenue of users when interacting with higher-level operators. Finally, case studies verify the effectiveness of our methods.