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Community Resilience Optimization Subject to Power Flow Constraints in Cyber-Physical-Social Systems in Power Engineering
arXiv - CS - Systems and Control Pub Date : 2020-04-02 , DOI: arxiv-2004.00772
Jaber Valinejad and Lamine Mili

This paper 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 multi-agent-based algorithm. The tool that makes the nexus between electricity generation on the physical side and the consumers and the critical loads 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. Simulation results reveal that a decrease in the initial values of the emotion, the risk perception, and the social media platform effect factor entails an increase in load shedding, which in turn results in a decrease in community resilience. In contrast, an increase in the initial values of cooperation, empathy, physical health, the capacity of microgrids and distributed energy resources results in a decrease in the load shedding, which in turn induces an enhancement of the community resilience.

中文翻译:

电力工程信息物理社会系统中受潮流约束的社区弹性优化

本文开发了一种受电力工程信息物理社会系统中潮流约束的社区弹性优化方法,该方法使用基于多代理的算法进行求解。使物理侧发电和消费者与社会侧关键负载之间建立联系的工具是潮流算法。具体来说,在考虑电力系统限制及其对关键负载(包括医院、避难所)的影响的同时,在提议的社区弹性优化方法中对消费者、产消者的情绪、同理心、合作和身体健康水平进行建模和加油站,仅举几例。优化解释了这样一个事实,即社会的满意度、生活水平、社会福祉取决于能源供应,包括电力供应。显然,由减载导致的电能缺乏对精神和心理生活质量都有影响,进而影响社区韧性。开发的约束社区弹性优化方法应用于两个案例研究,包括一个两区域 6 总线系统和一个修改的 IEEE RTS 24 总线系统。仿真结果表明,情绪初始值、风险感知和社交媒体平台效应因子的降低会导致减载增加,进而导致社区弹性降低。相比之下,合作、同理心、身体健康的初始值增加,
更新日期:2020-04-03
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