基于改进粒子群算法的输电线路舞动断线概率预测研究

Research on the Probability Prediction of Transmission Line Breakage by Galloping Based on Improved Particle Swarm Optimization Algorithm

【目的】为了解决冰风暴灾害下输电线路舞动断线问题,提出了基于改进粒子群算法的输电线路舞动断线概率预测模型。【方法】首先,采用改进粒子群算法确定输电线路在冰风暴灾害下风荷载与冰荷载的广义极值分布参数;其次,根据输电线路舞动的起舞风速和覆冰密度求取舞动情况下线路冰荷载和风荷载的极值分布。【结果】在此基础上,基于二元t-Copula连接函数计算线路舞动时风荷载和冰荷载的联合概率分布,实现了线路舞动断线的概率预测。【结论】结合湖南冬季输电线路舞动断线的历史数据,验证了改进粒子群算法的优越性和该模型的准确性,为输电线路舞动预报和指导线路提前部署防舞动措施提供了依据。

[Purposes]In order to solve the problem of transmission line breakage by galloping under ice storm,a probability prediction model of transmission line breaking based on improved particle swarm optimization(PSO)algorithm is proposed.[Methods]Firstly,the generalized extreme value(GEV)distribution parameters of wind load and ice load of transmission lines under ice storm disasters are determined by improved PSO algorithm;then,according to the wind speed and icing density of the transmission line galloping,the extreme value distribution of the ice load and wind load of the line under galloping is obtained.[Findings]Based on the binary t-Copula function,the joint probability distribution of ice load and wind load is obtained,and the probability prediction of transmission line breakage by galloping is realized.[Conclusions]Finally,using actual historical data of transmission line breakage by galloping in winter of Hunan Province,the superiority of the improved PSO algorithm and the accuracy of the proposed prediction model are verified,which can lay a foundation for transmission line breakage by galloping prediction and provide a basis for pre-deployment of anti-galloping measures.