An Intelligent Fault Diagnosis Approach for PV Array Based on SA-RBF Kernel Extreme Learning Machine - Details

author：

Indexed by：

Abstract：

In　this　paper,　based　on　an　improved　radial　basis　function　(RBF)　kernel　extreme　learning　machine　(ELM)　optimized　by　simulated　annealing　algorithm,　a　novel　intelligent　fault　diagnosis　approach　for　photovoltaic　(PV)　array　is　proposed.　Firstly,　three　common　PV　array　faults　are　analyzed　in　detailed.　And　then,　the　ELM　is　proposed　to　automatically　detect　the　faults　of　PV　array.　Moreover,　simulated　annealing　(SA)　algorithm　is　exploited　to　optimize　the　parameters　of　RBF-ELM　model.　Finally,　a　simulation　experiment　is　carried　out　to　verify　the　proposed　SA-RBF-ELM　and　the　result　shows　that　the　proposed　SA-RBF-ELM　approach　can　quickly　and　accurately　identify　the　typical　PV　faults　including　short　circuit,　aging　and　partial　shadow.　©　2017　The　Authors.

Keyword：

Failure analysis Fault detection Knowledge acquisition Machine learning Photovoltaic cells Radial basis function networks Simulated annealing

Community：

[ 1 ] [Wu, Yue]Institute of Micro-Nano Devices and Solar Cells, College of Physics and Information Engineering, Fuzhou University, 2 XueYuan Road, Fuzhou; 350116, China
[ 2 ] [Wu, Yue]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou; 213164, China
[ 3 ] [Chen, Zhicong]Institute of Micro-Nano Devices and Solar Cells, College of Physics and Information Engineering, Fuzhou University, 2 XueYuan Road, Fuzhou; 350116, China
[ 4 ] [Chen, Zhicong]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou; 213164, China
[ 5 ] [Wu, Lijun]Institute of Micro-Nano Devices and Solar Cells, College of Physics and Information Engineering, Fuzhou University, 2 XueYuan Road, Fuzhou; 350116, China
[ 6 ] [Wu, Lijun]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou; 213164, China
[ 7 ] [Lin, Peijie]Institute of Micro-Nano Devices and Solar Cells, College of Physics and Information Engineering, Fuzhou University, 2 XueYuan Road, Fuzhou; 350116, China
[ 8 ] [Lin, Peijie]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou; 213164, China
[ 9 ] [Cheng, Shuying]Institute of Micro-Nano Devices and Solar Cells, College of Physics and Information Engineering, Fuzhou University, 2 XueYuan Road, Fuzhou; 350116, China
[ 10 ] [Cheng, Shuying]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou; 213164, China
[ 11 ] [Lu, Peimin]Institute of Micro-Nano Devices and Solar Cells, College of Physics and Information Engineering, Fuzhou University, 2 XueYuan Road, Fuzhou; 350116, China

Reprint 's Address：

[chen, zhicong]institute of micro-nano devices and solar cells, college of physics and information engineering, fuzhou university, 2 xueyuan road, fuzhou; 350116, china;;[chen, zhicong]jiangsu collaborative innovation center of photovoltaic science and engineering, changzhou; 213164, china

Email：

zhicong.chen@fzu.edu.cn

Show more details

Related Keywords：

Research on vibration signal feature analysis and its fault diagnosis
2016，Electric Machines and Control
Lightning over-voltage fault identification of high-voltage transmission line based on correlation dimension and extreme learning machine
2016，High Voltage Engineering
Fault diagnosis of DAB converter based on Wavelet Packet-RBF Neural Network
2021，2021 China Automation Congress, CAC 2021
Unknown fault diagnosis of rolling bearing based on improved GWOLightGBM
2022，Journal of Aerospace Power
A novel fault diagnosis method for photovoltaic array based on BP-Adaboost strong classifier
2018，3rd International Conference on New Energy and Future Energy System, NEFES 2018

Source ：

ISSN： 1876-6102

Year： 2017

Volume： 105

Page： 1070-1076

Language： English

Cited Count：

WoS CC Cited Count：

SCOPUS Cited Count：

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 2

Affiliated Colleges：

Get Fulltext

DOI Library Discovery Baidu Scholar Search Engineering Village

Type
Departments

All Years Choose Year From to