Open Access

ARTICLE

Research on Asymmetric Fault Location of Wind Farm Collection System Based on Compressed Sensing

Huanan Yu¹, Gang Han^1,*, Hansong Luo², He Wang¹

1 Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education, Northeast Electric Power University, Jilin, 132012, China
2 Qinhuangdao Power Supply Company, State Grid Jibei Electric Power Co., Ltd., Qinhuangdao, 066099, China

* Corresponding Author: Gang Han. Email:

(This article belongs to the Special Issue: Wind Energy Development and Utilization)

Energy Engineering 2023, 120(9), 2029-2057. https://doi.org/10.32604/ee.2023.028365

Received 14 December 2022; Accepted 10 March 2023; Issue published 03 August 2023

Abstract

Aiming at the problem that most of the cables in the power collection system of offshore wind farms are buried deep in the seabed, which makes it difficult to detect faults, this paper proposes a two-step fault location method based on compressed sensing and ranging equation. The first step is to determine the fault zone through compressed sensing, and improve the data measurement, dictionary design and algorithm reconstruction: Firstly, the phase-locked loop trigonometric function method is used to suppress the spike phenomenon when extracting the fault voltage, so that the extracted voltage value will not have a large error due to the voltage fluctuation. Secondly, the λ-NIM dictionary is designed by using the node impedance matrix and the fault location coefficient to further reduce the influence of pseudo-fault points. Finally, the CoSaMP algorithm is improved with the generalized Jaccard coefficient to improve the reconstruction accuracy. The second step is to use the ranging equation to accurately locate the asymmetric fault of the wind farm collection system on the basis of determining the fault interval. The simulation results show that the proposed method is more accurate than the compressed sensing method and impedance method in fault section location and fault location accuracy, the relative error is reduced from 0.75% to 0.4%, and has a certain anti-noise ability.

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Keywords

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