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作 者:郝宗良 张韶华 HAO Zongliang;ZHANG Shaohua(State Grid Ningxia Electric Power Co.,Ltd.,Yinchuan 750001,China)
出 处:《电力需求侧管理》2023年第6期95-101,共7页Power Demand Side Management
基 金:国网宁夏电力有限公司咨询项目(8129NX180001)。
摘 要:为了有效界定停电事件的影响因素,提高应急情景动态推演模型的准确性,避免电力突发事故的发生,设计基于改进贝叶斯网络的大面积停电事件应急情景动态推演模型。首先,对初始情景、引发情景、爆发情景、恢复情景和消失情景等五个网络层级进行分析,构建大面积停电事件情景网络;其次,考虑应急决策主体、对象、目标、方案以及决策环境,模拟大面积停电事件应急决策过程,利用改进贝叶斯网络计算多层次情景网络之间移动概率,确定事件动态演化规律;最后,通过大面积停电事件数据的输入结果,得出包含大面积停电事件动态推演路径和最优应急方案。实验结果表明:应用设计模型后,停电面积缩小率为48.57%,停电事件的实际停电面积明显缩小。完善了应急情景动态推演过程,事件应急方案与实际停电情况相匹配,可以高效应对大面积停电事件,具有较高的应用价值。In order to effectively define the influencing factors of power outage events,improve the accuracy of emergency scenario dynamic deduction models,and avoid the occurrence of power emer-gencies,a large-scale power outage emergency scenario dynamic de-duction model based on improved Bayesian networks is designed.Firstly,five network levels of initial scenario,triggering scenario,outbreak scenario,recovery scenario,and disappearance scenario are analyzed to construct a large-scale power outage scenario net-work.Then,emergency decision-making subject,object,target,plan,and decision-making environment are considered,the emer-gency decision-making process of large-scale power outage events is simulated,improved Bayesian networks is used to calculate the prob-ability of movement between multi-level scenario networks,and the dynamic evolution law of events is determined.Finally,based on the input results of large-scale power outage event data,the dynamic in-ference path and optimal emergency plan including large-scale pow-er outage events are obtained.The experimental results show that af-ter applying the design model,the reduction rate of power outage ar-ea is 48.57%,and the actual power outage area of power outage events is significantly reduced.The dynamic deduction process of emergency scenarios has been improved,and the emergency re-sponse plan is matched with the actual power outage situation,which can efficiently respond to large-scale power outage events and has high application value.
关 键 词:改进贝叶斯网络 大面积停电事件 应急情景 动态推演 应急方案
分 类 号:TM73[电气工程—电力系统及自动化] TM08
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