A MOPSO based faulty section location method for distribution networks with PVs

2017 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) Pub Date : 2017-11-01 DOI:10.1109/APPEEC.2017.8308948

Fan Wu, Jin-quan Zhao, Bin Zhu, Haiwei Wu, Dawei Su

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引用次数: 3

Abstract

The distributed generations (DGs) make the establishment of switch function complex, and the faulty section location methods for traditional distribution networks are no longer applicable. In order to improve the rapidity and accuracy of faulty section location, a Multi-Objective Particle Swarm Optimization (MOPSO) based faulty section location method for distribution networks with photovoltaic (PV) generations is proposed. The influence of fault current characteristics of PV generations under different light intensities is taken into account. Switch function for dynamic switching of PV generations is proposed. Since the single objective optimization intelligence algorithms easily cause the premature convergence and the computational complexity of the NSGA-II algorithm is high, the MOPSO algorithm is used to solve the problem, which can avoid the determination of the weighting factors. The simulation results show that the proposed method improves the rapidity and accuracy of location effectively, and has superior fault-tolerance to distortion information.

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基于MOPSO的带pv配电网故障区段定位方法

分布式代(dg)使开关函数的建立变得复杂，传统的配电网故障区段定位方法不再适用。为了提高故障区段定位的快速性和准确性，提出了一种基于多目标粒子群优化(MOPSO)的光伏发电配电网故障区段定位方法。考虑了不同光照强度下光伏发电机组故障电流特性的影响。提出了用于光伏发电动态切换的开关函数。由于单目标优化智能算法容易导致过早收敛，且NSGA-II算法的计算复杂度较高，采用MOPSO算法解决该问题，避免了权重因子的确定。仿真结果表明，该方法有效地提高了定位的快速性和准确性，并对畸变信息具有较好的容错性。

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2017 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

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