Chrome Extension
WeChat Mini Program
Use on ChatGLM

A New Traveling Wave Location Method for Wide Area Power Grid Based on Fault Line Trust Region and Second Path Traveling Wave

Wanglong Wan,Zheng Qin, Minggao Deng,Yu Liu

Electric Power Systems Research(2025)

Hunan University | Hunan Xiangneng Intelligent Electric Appliance Co.

Cited 0|Views6
Abstract
A novel traveling wave-based fault location method utilizing the second-path traveling wave is proposed to tackle the dead zone issue in wide-area power systems caused by ring network configurations. Firstly, an analysis of ring-shaped transmission networks reveals the emergence of dead zones on both sides of faulted lines due to the ring topology. Subsequently, an extension of the basic ring network structure is proposed, introducing a method to compute the credible region for any network topology. Lastly, in cases where the fault location results fall within the non-credible region, the ESMD-TEO method is employed to accurately identify the second-path traveling wave. Fault location calculation is then conducted based on this identified wave, replacing the results from the non-credible region. A linear fit is performed on all credible location results to achieve precise fault localization. Simulation and practical application results demonstrate the effectiveness of this method in mitigating dead zones in fault location within ring networked transmission systems, thereby enhancing the accuracy of wide-area traveling wave-based fault localization with strong robustness, achieving a location error of less than 100 meters.
More
Translated text
Key words
Fault localization,Wide area power grid,Second path traveling wave,ESMD-TEO
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper

要点】:本文提出了一种基于故障线路信任区域和次路径行波的新颖行波故障定位方法,有效解决了宽域电网中环形网络配置导致的故障定位死区问题,实现了小于100米的定位误差。

方法】:方法首先分析了环形传输网络中故障线路两侧死区的形成原因,然后扩展了基本环形网络结构,提出了一种计算任意网络拓扑可信区域的方法。对于定位结果落在不可信区域的情况,采用ESMD-TEO方法准确识别次路径行波,并基于该行波进行故障定位计算。

实验】:通过模拟和实际应用测试,验证了该方法在环形网络传输系统中减少故障定位死区的有效性,实验数据集未具体提及,但结果显示定位误差小于100米。