基于IPOA- LSSVM模型的高压直流输电线路故障定位
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西安科技大学

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陕西省自然科学基础研究计划资助项目(2021JM-393)。


Fault location of HVDC transmission line based on IPOA-LSSVM model
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西安科技大学

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    摘要:

    故障定位在长距离高压直流输电系统中起着至关重要的作用,针对线路衰减系数计算不准和二次波头难以捕捉的问题,提出了一种改进鹈鹕优化算法(IPOA)优化最小二乘支持向量(LSSVM)的故障定位模型。首先根据行波衰减原理,推导故障距离和线路两端线模分量模极大值比的计算公式,发现二者具有非线性关系。其次使用LSSVM泛化二者之间的关系,将改进后的POA算法对LSSVM的关键参数进行寻优,建立了IPOA- LSSVM故障定位模型。通过在两端采集故障信号,对其进行小波变换得到首波头幅值比作为模型的输入量,故障距离作为输出量进行仿真验证。仿真结果表明,该模型不受过渡电阻和故障类型的影响,能够可靠准确的定位。

    Abstract:

    Fault location plays an important role in long distance HVDC transmission system. To solve the problems of inaccurate attenuation coefficient calculation and difficult capture of secondary wave head, a fault location model based on improved Pelican optimization algorithm (IPOA) and optimized least squares support vector Machine (LSSVM) is proposed. Firstly, according to the attenuation principle of traveling wave, the formula of fault distance and modulus maximum ratio of two terminal mode components of the line is derived, and the nonlinear relationship between them is found. Secondly, using LSSVM to generalize the relationship between the two, the improved POA algorithm is used to optimize the key parameters of LSSVM, and the IPOA-LSSVM fault location model is established. By collecting fault signals at both ends, the amplitude ratio of the first wave head is obtained as the input of the model, and the fault distance is used as the output for simulation verification. The simulation results show that the model is not affected by the transition resistance and fault type, and can locate reliably and accurately.

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商立群.基于IPOA- LSSVM模型的高压直流输电线路故障定位[J].南京信息工程大学学报,,():

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  • 收稿日期:2023-10-09
  • 最后修改日期:2024-03-03
  • 录用日期:2024-03-05
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