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基于压缩感知的电网传输线故障定位方法 被引量:1

A Fault Location Method For Grid Transmission Line Based on Compressed Sensing
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摘要 文中提出了一种基于压缩感知稀疏重构技术的广域故障定位方法,用于准确定位传输网络中的单故障和双故障位置.与早期传统的故障定位方法不同,该方法只需要通过相量测量单元(PMU)在数量有限的节点中测量即可实现故障定位.测量得到的电压相量和电网的阻抗矩阵产生一个欠定方程组,可以通过压缩感知稀疏重构的方法求解.重构得到了一个稀疏故障电流矢量,通过其中的非零元素判断可能的故障区域.对于没有故障的区域,可以由PMU测量到的电流相量计算相邻节点的电压,然后用新计算的电压和PMU测量值确定故障线路.利用替代定理和最小二乘法计算发生故障前后的节点电压变化量和故障线路两端的电流变化量.文中针对几种典型的故障类型,基于压缩感知和改进的传输线方程精确估计故障位置,消除了复杂的数学迭代过程,进一步提高了故障定位精度.应用PSCAD仿真软件在IEEE39节点系统上进行算例仿真,对故障定位算法进行了测试研究,验证该算法可以实现常见故障的精确定位. This paper proposes a wide-area fault location method based on compressed sensing sparse reconstruction method,which is used to accurately locate single and double fault in transmission networks.Different from the traditional fault location method,we only needs to measure the fault location by measuring the phasor measurement unit(PMU)in a limited number of buses.The measured voltage phasor and the impedance matrix of the transmission network yield an undetermined system of equations that can be solved by sparse reconstruction methods.The reconstruction yields a sparse fault current vector through which non-zero elements are used to determine possible fault regions.For areas with no faults,the voltage of adjacent buses can be calculated from the current phasors measured by the PMU,and then the fault line can be estimated using the newly calculated voltage and PMU measurement data.The substitution theorem and the least squares method are used to calculate the changes between pre-and during-fault voltages,and currents in both ends of the fault lines.For several typical fault types,the fault location is accurately estimated based on the compressed sensing and improved transmission line equations.The algorithm eliminates complex mathematical iterative processes and further improves the positioning accuracy.The PSCAD simulation software is used to simulate the example on the IEEE39 bus system.The fault location algorithm is tested and verified,which proves that the algorithm can accurately locate common faults.
作者 于华楠 白晓斐 王鹤 Yu Huanan;Bai Xiaofei;Wang He(Electrical Engineering College,Northeast Electric Power University,Jilin Jilin 132012)
出处 《东北电力大学学报》 2020年第1期47-55,共9页 Journal of Northeast Electric Power University
基金 国家重点研发计划(2016YFB0901200) 吉林省科技厅项目(20160520089JH)。
关键词 压缩感知 PMU l1范数最小化 替代定理 故障定位 Compressed sensing PMU Lj-norm minimization Substitution theorem Fault location
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