Online photovoltaic fault detection method based on data stream clustering - Details

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As　the　core　component　of　solar　power　station,　PV　array　is　particularly　important　for　safe　and　stable　operation　of　the　entire　system.　The　existence　of　PV　array　faults　for　a　long　time　can　lead　to　potential　danger　of　the　entire　PV　system.　Since　the　PV　data　is　greatly　affected　by　the　environment,　the　continuous　data　stream　generated　during　the　operation　of　PV　arrays　can　form　clusters　of　arbitrary　shape.　When　a　PV　fault　occurs,　new　data　streams　can　form　a　cluster　that　is　different　from　the　one　under　normal　operation.　Accordingly,　this　paper　presents　a　model　for　online　fault　detection　of　PV　arrays　faults　using　data　stream　clustering　approach.　The　real-time　data　stream　of　the　PV　arrays　is　transmitted　to　the　diagnostic　system　through　RabbitMQ　server　for　online　detection　and　data　storage.　The　online　density-based　spatial　clustering　of　applications　with　noise　(DBSCAN)　algorithm　is　used　for　clustering　the　data.　Then,　the　faults　are　detected　by　judging　whether　new　clusters　are　formed.　The　experiment　result　shows　the　effectiveness　of　the　proposed　method　in　grid-connected　PV　system.　©　2020　IOP　Publishing　Ltd.　All　rights　reserved.

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[ 1 ] [Cai, Y.]School of Physics and Information Engineering, Institute of Micro-Nano Devices and Solar Cells, Fuzhou University, Fuzhou, China
[ 2 ] [Cai, Y.]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou, China
[ 3 ] [Lin, P.]School of Physics and Information Engineering, Institute of Micro-Nano Devices and Solar Cells, Fuzhou University, Fuzhou, China
[ 4 ] [Lin, P.]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou, China
[ 5 ] [Lin, Y.]College of Computer and Information Sciences, Fujian Agriculture and Forest University, Fuzhou, China
[ 6 ] [Zheng, Q.]School of Physics and Information Engineering, Institute of Micro-Nano Devices and Solar Cells, Fuzhou University, Fuzhou, China
[ 7 ] [Zheng, Q.]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou, China
[ 8 ] [Cheng, S.]School of Physics and Information Engineering, Institute of Micro-Nano Devices and Solar Cells, Fuzhou University, Fuzhou, China
[ 9 ] [Cheng, S.]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou, China
[ 10 ] [Chen, Z.]School of Physics and Information Engineering, Institute of Micro-Nano Devices and Solar Cells, Fuzhou University, Fuzhou, China
[ 11 ] [Chen, Z.]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou, China
[ 12 ] [Wu, L.]School of Physics and Information Engineering, Institute of Micro-Nano Devices and Solar Cells, Fuzhou University, Fuzhou, China
[ 13 ] [Wu, L.]Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou, China

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IOP Conference Series: Earth and Environmental Science

ISSN： 1755-1307

Year： 2020

Issue： 1

Volume： 431

Language： English

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SCOPUS Cited Count： 1

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