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Quantitative Prediction Method for Distribution Power Grid Risk

Authors :
Xuesong Tang
Bin Wu
Guangming Yu
Jianwei Zou
Han Zhou
Di Xie
Yingxu Jin
Source :
E3S Web of Conferences, Vol 236, p 01014 (2021)
Publication Year :
2021
Publisher :
EDP Sciences, 2021.

Abstract

The electric power distribution grid is directly oriented to the majority of the ordinary users. Traditional operation and maintenance are performed mainly based on experience, which disable to rationally evaluate the status of the line and predict faults. Based on big data, the risk of the line is evaluated through principal component analysis in this paper, so that a machine learning algorithm is carried out to calculate the risk value of the distribution grid line unit. Finally, GA-BP neural network is used to build a line risk value prediction model for improvement.

Subjects

Subjects :
Environmental sciences
GE1-350

Details

Language :
English, French
ISSN :
22671242
Volume :
236
Database :
Directory of Open Access Journals
Journal :
E3S Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.93db5799ce42bd933988b2ee38d14a
Document Type :
article
Full Text :
https://doi.org/10.1051/e3sconf/202123601014