Fault Diagnosis Method of Photovoltaic Array Based on BP Neural Network

被引：0
|
作者：
Wang, Junjie [1 ]
Wang, Shan [1 ]
Liu, Haixiong [1 ]
Hong, Jianbo [2 ]
Gao, Dedong [1 ,2 ]
机构：
[1] Qinghai Univ, Sch Mech Engn, Xining 810016, Peoples R China
[2] Haixi Huahui Chem & Machinery Co LTD, Qinghai, Peoples R China
来源：
2019 3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS AND TECHNOLOGIES (AIAAT 2019) | 2019年 / 646卷
基金：
中国国家自然科学基金;
关键词：
POWER-POINT TRACKING; MODEL;
D O I：
10.1088/1757-899X/646/1/012020
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Photovoltaic arrays are prone to various failures due to long-term work. In order to quickly and accurately diagnose the type of failure of the PV array and implement online monitoring of the PV array, this paper proposes the BP neural network for PV array fault diagnosis, and proposes a network search method when training BP neural network. And the K-cross-validation method is used to select the number of hidden layer nodes. The BP neural network fault diagnosis model designed and trained by this method is proved to have high precision.
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收藏
页数：10
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