Supervised relevance vector machine based dynamic disturbance classifier for series compensated transmission line,International Transactions on Electrical Energy Systems

当前位置： X-MOL 学术 › Int. Trans. Electr. Energy Syst. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Supervised relevance vector machine based dynamic disturbance classifier for series compensated transmission line
International Transactions on Electrical Energy Systems ( IF 1.9 ) Pub Date : 2020-10-10 , DOI: 10.1002/2050-7038.12663
Ujjaval Patel ₁ , Nilesh Chothani ₁ , Praghnesh Bhatt ₂

Affiliation

Background: Nowadays, numerical relays configured through power swing blocking function are vulnerable to faults with high impedance owing to nonlinearities present in the faulty path. Identification of symmetrical high impedance faults incepting during the power swing scenario is of prime importance for protection engineers to avoid cascade tripping. It is analyzed that the classical approaches for symmetrical fault detection during power swing can mal-operate owing to high level of uncertainty arise during validation of high impedance fault, symmetrical faults and cross country faults during power swing with varied level of compensation which has been explored in this research.

中文翻译：

基于有监督相关向量机的串补输电线路动态扰动分类器

背景：如今，由于故障路径中存在非线性，通过功率摆动阻塞功能配置的数字继电器容易受到高阻抗故障的影响。在电力摆幅情况下识别对称高阻抗故障对于保护工程师避免级联跳闸至关重要。分析了电力摆动期间对称故障检测的经典方法可能会由于高水平的不确定性而出现故障在这项研究中。

更新日期：2020-10-10

点击分享查看原文

点击收藏

阅读更多本刊最新论文本刊介绍/投稿指南11