Graph Theory-Based Fault Location Method for Transmission Systems With Renewable Energy Sources

IF 3.3 Q3 ENERGY & FUELS IEEE Open Access Journal of Power and Energy Pub Date : 2024-11-27 DOI:10.1109/OAJPE.2024.3507537
Victor Gonzalez;V. Torres-García;Daniel Guillen;Luis M. Castro
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Abstract

Fault location has been crucial in minimizing fault restoration time. Various techniques and methodologies have been deployed to enhance the performance of fault location algorithms, especially in light of the increasing integration of renewable energy sources. In this context, this paper describes a graph-theory-based method for fault location in power networks with renewable energy sources. This novel technique is designed to provide accurate fault distance estimates, even in the presence of severe noise and fault resistance. It takes advantage of graph theory and equivalent impedances applying Kirchhoff’s laws systematically to ensure accurate fault location even in the presence of fault resistances. To showcase the improved accuracy of the proposed methodology, a comparison with typical impedance-based two-terminal fault location methods is carried out. The effectiveness of the proposed algorithm was proven with different electrical systems. Average errors inferior to 0.22% and 0.48% were obtained for single-phase faults and three-phase faults with resistances up to $200~\Omega $ respectively, which confirms the improved performance with respect to conventional algorithms implemented in typical impedance relays.
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基于图论的可再生能源输电系统故障定位方法
故障定位是减少故障恢复时间的关键。各种技术和方法被用于提高故障定位算法的性能,特别是考虑到可再生能源的日益整合。在此背景下,本文提出了一种基于图论的可再生能源电网故障定位方法。这种新技术的目的是提供准确的故障距离估计,即使在存在严重的噪声和故障阻力。它利用图论和等效阻抗,系统地应用基尔霍夫定律,即使在存在故障电阻的情况下也能保证准确的故障定位。为了证明该方法的准确性,与典型的基于阻抗的双端故障定位方法进行了比较。在不同的电气系统中验证了该算法的有效性。单相故障和三相故障的平均误差分别小于0.22%和0.48%,电阻为$200~\Omega $,与典型阻抗继电器的传统算法相比,该算法的性能有所提高。
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来源期刊
CiteScore
7.80
自引率
5.30%
发文量
45
审稿时长
10 weeks
期刊最新文献
Advancing Coherent Power Grid Partitioning: A Review Embracing Machine and Deep Learning Information for authors Synergistic Meta-Heuristic Adaptive Real-Time Power System Stabilizer (SMART-PSS) IEEE Open Access Journal of Power and Energy Publication Information 2025 Index IEEE Open Access Journal of Power and Energy Vol. 11
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