融合信息物理社会因素的配电网可靠性评估方法OA北大核心CSTPCD
Reliability Assessment Method for Distribution Network Incorporating Cyber-Physical-Social Factors
为分析重大社会活动中信息系统先进技术和社会系统应急保电措施对配电网可靠性的影响,文中提出融合信息物理社会因素的配电网可靠性评估方法.首先,为分析信息物理社会系统的相互作用,构建了配电网可靠性的信息物理社会交互框架.然后,通过构建设备发展型和破坏型故障状态转移模型,量化了信息系统中缺陷诊断、风险预警技术作用周期以及社会系统中检修人员技术水平与设备故障率的关系.通过构建设备故障恢复时间模型,量化了信息系统中故障定位技术精度以及社会系统中交通路况、应急物资充裕度与设备故障恢复时间的关系.最后,为了验证框架和模型的有效性,文中建立了一个包含信息物理社会系统基本信息的测试系统.结果验证了信息、社会系统对配电物理系统可靠性的提升作用.
This paper proposes a reliability evaluation method for the distribution network incorporating cyber-physical-social factors to analyze the influence of advanced technology in cyber systems and the emergency conservation measures in social systems in the major social events on the reliability of the distribution network.First,in order to analyze the interaction of cyber-physical-social systems(CPSS),this paper constructs a CPSS interactive framework for distribution network reliability.Then,by constructing the equipment developmental and destructive fault state transition models,it quantifies the relationship between the defect diagnosis and action period of risk warning technology in the cyber system as well as the technical level of overhauling personnel and the equipment fault rate in the social system.By constructing the equipment fault recovery time model,it quantifies the relationship between the accuracy of fault location technology in the cyber system and the traffic road condition,the sufficiency of emergency supplies and the equipment fault recovery time in the social system.Finally,to verify the effectiveness of the framework and models,this paper establishes a test system containing the basic information of CPSS.The results validate the role of cyber and social systems in enhancing the reliability of the distribution physical systems.
卢俞帆;刘念;高舜安
新能源电力系统国家重点实验室(华北电力大学),北京市 102206国网冀北电力有限公司,北京市 100054
配电网可靠性评估信息物理社会系统缺陷诊断应急保电
distribution networkreliability evaluationcyber-physical-social system(CPSS)defect diagnosisemergency electricity conservation
《电力系统自动化》 2024 (003)
51-61 / 11
国家重点研发计划资助项目(2020YFF0305800). This work is supported by National Key R&D Program of China(No.2020YFF0305800).
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