4.6 Article

A new passive islanding detection approach using wavelets and deep learning for grid-connected photovoltaic systems

期刊

ELECTRIC POWER SYSTEMS RESEARCH
卷 199, 期 -, 页码 -

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2021.107437

关键词

Deep learning; Renewable distributed energy resources; Passive islanding detection smart grid

资金

  1. Natural Sciences and Engineering Research Council of Canada

向作者/读者索取更多资源

This paper introduces a passive islanding detection approach that uses deep learning combined with the continuous wavelet transform, which can effectively solve the islanding detection problem without needing to identify islanding features in advance.
The renewable-based distributed energy resources (R-DERs) are extensively used in the smart distribution systems. Despite the advantages of the R-DER, they also introduce some operational challenges such as the unintentional islanding, reverse power flow, and several protection issues. Due to the unpredictable faults, an island or multiple islands can be formed throughout the electrical power systems. The island may have R-DER that shall be tripped within 2 s of the islanding formation as per IEEE 1547 and hence the islanding must be detected. This paper introduces a passive islanding detection approach that uses deep learning combined with the continuous wavelet transform and hence no need for identifying the islanding features a priori as in the existing islanding detection approaches. The numerical examples demonstrating the effectiveness of the proposed approach are presented and the conclusion is drawn.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据