电网技术2012，Vol.36Issue(4)：213-218,6.
冰风暴灾害下输电线路故障概率预测
Probabilistic Prediction of Transmission Line Fault Resulted from Disaster of Ice Storm
摘要
Abstract
In allusion to transmission line fault resulted from the disaster of ice storm, based on extreme learning machine （ELM） and Copula function a probabilistic prediction model for transmission line breakage and tower topple over is proposed. By use of generalized extreme value （GEV） distribution, the proposed model depicts the probabilistic characteristics of excessive freezing rainfall, wind speed, wind load and ice load of transmission line and tower under the disaster of ice storm, and by means of FLM network the varying parameters of GEV distribution＇s shape scale and location are predicted, and then considering probability correlation between wind load and ice load and by means of Clayton-Copula function the joint probability distribution of ice load and wind load is established, thus the realtime fault probability prediction of transmission line and towers is implemented. Based on historical data of Chenzhou power network in Hunan province, both effectiveness and accuracy of the proposed prediction method are verified by the results of calculation example.关键词
极端学习机/广义极值/Clayton—Copula函数/输电线路/故障概率/冰风暴Key words
extreme learning machine (ELM)/generalized extreme value (GEV)/Clayton-Copula function/transmission lines, fault probability/ice storm分类
信息技术与安全科学引用本文复制引用
杨洪明,黄拉,何纯芳,易德鑫..冰风暴灾害下输电线路故障概率预测[J].电网技术,2012,36(4):213-218,6.基金项目
国家自然科学基金 （）
湖南省杰出青年科学基金 （）
教育部新世纪优秀人才支持计划 （）
湖南省高校创新平台开放基金（10K003）. （）
