AI in arcing-HIF detection: A brief review

18Citations
Citations of this article
21Readers
Mendeley users who have this article in their library.

Abstract

In the past few decades, the arcing-high-impedance fault (arcing-HIF) detection problems have become an important issue in the effectively grounded distribution network. Many solutions have been proposed to address this problem. The most attractive way is artificial intelligence (AI) method. The paper gives a comprehensive review of arcing-HIF detection in distribution network-based AI. First, characteristics and models of arcing-HIF are analysed, the arcing-HIF database construction method is also explained; this part is a foundation work for arcing-HIF detection. Next, arcing-HIF detection methods based AI are summarised in details including data acquisition, feature extraction and classifier selection. Then, a set of criteria are proposed to evaluate the reliability of arcing-HIF detection algorithm. Finally, the future trends and challenges to arcing-HIF detection are also fully accounted. This review can be a valuable guide for researchers who are interested in arcing- HIF detection-based AI.

Cite

CITATION STYLE

APA

Hao, B. (2020, August 1). AI in arcing-HIF detection: A brief review. IET Smart Grid. Institution of Engineering and Technology. https://doi.org/10.1049/iet-stg.2019.0091

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free