Community Resilience Optimization Subject to Power Flow Constraints in Cyber-Physical-Social Systems

This article develops a community resilience optimization method subject to power flow constraints in the cyber-physical-social systems in power engineering, which is solved using a multiagent-based algorithm. The tool that makes the nexus between the electric generation on the physical side and consumers and prosumers on the social side is the power flow algorithm. Specifically, the levels of emotion, empathy, cooperation, and the physical health of the consumers, prosumers are modeled in the proposed community resilience optimization approach while accounting for the electric power system constraints and their impact on the critical loads, which include hospitals, shelters, and gas stations, to name a few. The optimization accounts for the fact that the level of satisfaction of the society, the living standards, and the social well-being are depended on the supply of energy, including electricity. Evidently, the lack of electric energy resulting from load shedding has an impact on both the mental and the psychical quality of life, which in turn affects the community resilience. The developed constrained community resilience optimization method is applied to two case studies, including a two-area 6-buses system and a modified IEEE RTS 24-bus system.