摘要
当前针对电力系统的事故分析多以单一因素为重点,未全面考虑电力系统风险影响因素耦合带来的新问题,较易产生疏漏。在深入剖析电力系统实际运行环境与事故致因理论的基础上,文章首先提出基于“认知–约束”的电力系统事故机理分析模型,从人为因素、设备因素、管理因素、环境因素等方面对电力系统安全风险的起源进行系统分析;然后,进一步构建基于Petri网的事故树分析方法,对影响电力系统安全的关键因素进行量化分析;最后,基于电力系统事故案例对所述方法进行模型构建,并计算各因素的结构重要度,初步掌握事故发生的规律,与实际电力系统事故综合分析结果的对比表明,所述模型具有良好的可用性。该研究成果对科学合理避免电力系统事故发生、建设安全电网具有一定的参考借鉴意义。
At present,the accident analysis of power system mostly focuses on a single factor,and does not fully consider the new problems caused by the coupling of power system risk influencing factors.Based on the in-depth analysis of the actual operation environment of power system and the theory of accident causes,this paper first presents an analysis model of power system accident mechanism based on "cognitive-constraint",and systematically analyzes the origin of power system security risk from the aspects of human factors,equipment factors,management factors and environmental factors.Then,the fault tree analysis method based on Petri net is further constructed to quantitatively analyze the key factors affecting power system security.Finally,based on the power system accident cases,the model of the method is constructed,the structural importance of each factor is calculated,and the law of accident occurrence is preliminarily mastered.The comparison with the comprehensive analysis results of actual power system accidents shows that the model has good effectiveness and availability.The research results have certain reference significance for scientifically and reasonably avoiding power system accidents and building a safe power grid.
作者
李刚
赵琳颖
吕进
LI Gang;ZHAO Linying;LV Jin(Department of Computer,North China Electric Power University,Baoding 071003,China;Engineering Research Center of Intelligent Computing for Complex Energy Systems,Ministry of Education,Baoding 071003,China;Nanjing NARI Information and Communication Technology,Co.,Ltd.,Nanjing 211100,China)
出处
《电力信息与通信技术》
2022年第4期70-78,共9页
Electric Power Information and Communication Technology
基金
国家电网有限公司科技项目“基于安全域核心业务数据关联评估模型及应用研究”(SGJSWX00F ZJS1901915)
国家自然科学基金项目(51407076)
中央高校基本科研业务费专项资金资助(2020MS119)。
