基于人工神经网络和网络迁移的双端输电线路非同步故障测距算法OACSCDCSTPCD
Asynchronous Fault Location Algorithm for Two-terminal Transmission Lines Based on Artificial Neural Network and Network Migration
现有双端输电线路故障测距方法或依赖于线路模型和线路参数,亦或依赖于大量历史故障数据.为了解决上述问题,该文首先分析总结了分布参数模型和Π型线路模型的测距原理,根据线路故障前后的两端正序电压和正序电流构造了双端输电线路的测距函数;然后在此基础上提出了一种基于人工神经网络与网络迁移的双端输电线路非同步故障测距算法,所提算法不依赖于线路模型和线路参数;最后在Matlab/Simulink平台上搭建了 500kV输电线路仿真模型,验证了所提算法的正确性和…查看全部>>
The current algorithms of the two-terminal transmission line fault location rely either on the line models and the line parameters,or on the large amounts of historical fault data.To solve this problem,first by summarizing the fault location principles of the distributed parameter model and theΠ-type model,this paper establishes the fault location function of the two-terminal transmission line according to the positive sequence voltage and the positive seque…查看全部>>
陈晓龙;孙丽蓉;李永丽;李斌
智能电网教育部重点实验室(天津大学),天津市南开区 300072智能电网教育部重点实验室(天津大学),天津市南开区 300072智能电网教育部重点实验室(天津大学),天津市南开区 300072智能电网教育部重点实验室(天津大学),天津市南开区 300072
动力与电气工程
双端输电线路故障测距人工神经网络网络迁移非同步数据
two-terminal transmission linesfault locationartificial neural networknetwork migrationasynchronous data
《电网技术》 2023 (12)
5169-5180,12
国家自然科学基金委员会-国家电网公司智能电网联合基金资助项目(U2066210).Project Supported by National Natural Science Foundation of China-State Grid Joint Fund for Smart Grid(U2066210).
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