使用自适应性神经模糊推理系统对高频直流线进行增强的距离保护
A M Hamada1, M I Abdel-Fattah2, Ali M El-Rifaie3
1Railway Department, Faculty of Industrial and Energy Technology, Borg El-Arab Technological University, Alexandria, Egypt.
PloS one
|January 6, 2026
概括
本研究引入了一种新的模糊逻辑方法,用于快速准确地检测,分类和定位高压直流传输线 (HVDC-TLs) 的故障. 该方法提高了保护系统的性能,并优于现有技术.
科学领域:
- 电气工程 电气工程
- 电力系统工程 电力系统工程
背景情况:
- 准确和快速的故障检测对于直流传输系统的可靠运行至关重要.
- 对于高压直流输电线路 (HVDC-TLs) 的现有方法在检测故障方面面临挑战,特别是那些具有高电阻的故障.
研究的目的:
- 提出一种用于HVDC-TLs故障检测,分类和定位的新方法.
- 提高HVDC-TL的保护方案的性能和可靠性.
主要方法:
- 使用模糊推理系统 (FIS) 开发了一个远程保护方案.
- 一个自适应的神经模糊推断系统 (ANFIS) 被训练为精确的故障位置估计.
- 输电线路被划分为三个区域用于故障位置的识别.
- 在单极直流传输线模型上使用PSCAD和MATLAB进行模拟.
主要成果:
- 拟议的FIS模型有效地检测和分类故障,包括那些具有高阻力的故障.
- 该ANFIS准确地估计了每公里的故障位置.
- 与现有方法相比,开发的远程保护方案显示出更高的性能.
结论:
- 这种基于模糊推理的新方法为HVDC-TLs的故障管理提供了更好的准确性和速度.
- 该方法有效估计故障区域和定位故障,提高整体系统保护.
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