Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier
F C Han, Z C Chen, L J Wu, J L Yu, C Long, P J Lin, S Y Cheng and F P Su
Institute of Physics (IOP)
Published 2018
Institute of Physics (IOP)
Published 2018
Publication Date: |
2018-10-31
|
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Publisher: |
Institute of Physics (IOP)
|
Print ISSN: |
1755-1307
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Electronic ISSN: |
1755-1315
|
Topics: |
Geography
Geosciences
Physics
|
Published by: |
_version_ | 1836399075998564352 |
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autor | F C Han, Z C Chen, L J Wu, J L Yu, C Long, P J Lin, S Y Cheng and F P Su |
beschreibung | This paper presents a novel fault detection method for photovoltaic (PV) array using an improved two-stage Hampel identifier, which can quickly detect the occurrence of faults and locate them at PV module level. The fault detection method is implemented in a two-level wireless sensor network based distributed on-line monitoring system which is developed to monitor the voltage of each PV module and current of all parallel PV strings in real-time. The 1 st stage Hampel identifier detects and locates the faulty PV strings by comparing the instantaneous currents of different PV strings. The 2 nd stage Hampel identifier detects and locates the faulty PV modules by comparing the instantaneous voltages of different PV modules in the faulty strings. Experimental results show that the proposed method can successfully detect and locate faulty strings and modules in several faulty cases, including the line-line faults, the degradation faults, the partial shading faults ... |
citation_standardnr | 6350435 |
datenlieferant | ipn_articles |
feed_id | 108844 |
feed_publisher | Institute of Physics (IOP) |
feed_publisher_url | http://www.iop.org/ |
insertion_date | 2018-10-31 |
journaleissn | 1755-1315 |
journalissn | 1755-1307 |
publikationsjahr_anzeige | 2018 |
publikationsjahr_facette | 2018 |
publikationsjahr_intervall | 7984:2015-2019 |
publikationsjahr_sort | 2018 |
publisher | Institute of Physics (IOP) |
quelle | IOP Conference Series: Earth and Environmental Science |
relation | http://iopscience.iop.org/1755-1315/188/1/012063 |
search_space | articles |
shingle_author_1 | F C Han, Z C Chen, L J Wu, J L Yu, C Long, P J Lin, S Y Cheng and F P Su |
shingle_author_2 | F C Han, Z C Chen, L J Wu, J L Yu, C Long, P J Lin, S Y Cheng and F P Su |
shingle_author_3 | F C Han, Z C Chen, L J Wu, J L Yu, C Long, P J Lin, S Y Cheng and F P Su |
shingle_author_4 | F C Han, Z C Chen, L J Wu, J L Yu, C Long, P J Lin, S Y Cheng and F P Su |
shingle_catch_all_1 | Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier This paper presents a novel fault detection method for photovoltaic (PV) array using an improved two-stage Hampel identifier, which can quickly detect the occurrence of faults and locate them at PV module level. The fault detection method is implemented in a two-level wireless sensor network based distributed on-line monitoring system which is developed to monitor the voltage of each PV module and current of all parallel PV strings in real-time. The 1 st stage Hampel identifier detects and locates the faulty PV strings by comparing the instantaneous currents of different PV strings. The 2 nd stage Hampel identifier detects and locates the faulty PV modules by comparing the instantaneous voltages of different PV modules in the faulty strings. Experimental results show that the proposed method can successfully detect and locate faulty strings and modules in several faulty cases, including the line-line faults, the degradation faults, the partial shading faults ... F C Han, Z C Chen, L J Wu, J L Yu, C Long, P J Lin, S Y Cheng and F P Su Institute of Physics (IOP) 1755-1307 17551307 1755-1315 17551315 |
shingle_catch_all_2 | Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier This paper presents a novel fault detection method for photovoltaic (PV) array using an improved two-stage Hampel identifier, which can quickly detect the occurrence of faults and locate them at PV module level. The fault detection method is implemented in a two-level wireless sensor network based distributed on-line monitoring system which is developed to monitor the voltage of each PV module and current of all parallel PV strings in real-time. The 1 st stage Hampel identifier detects and locates the faulty PV strings by comparing the instantaneous currents of different PV strings. The 2 nd stage Hampel identifier detects and locates the faulty PV modules by comparing the instantaneous voltages of different PV modules in the faulty strings. Experimental results show that the proposed method can successfully detect and locate faulty strings and modules in several faulty cases, including the line-line faults, the degradation faults, the partial shading faults ... F C Han, Z C Chen, L J Wu, J L Yu, C Long, P J Lin, S Y Cheng and F P Su Institute of Physics (IOP) 1755-1307 17551307 1755-1315 17551315 |
shingle_catch_all_3 | Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier This paper presents a novel fault detection method for photovoltaic (PV) array using an improved two-stage Hampel identifier, which can quickly detect the occurrence of faults and locate them at PV module level. The fault detection method is implemented in a two-level wireless sensor network based distributed on-line monitoring system which is developed to monitor the voltage of each PV module and current of all parallel PV strings in real-time. The 1 st stage Hampel identifier detects and locates the faulty PV strings by comparing the instantaneous currents of different PV strings. The 2 nd stage Hampel identifier detects and locates the faulty PV modules by comparing the instantaneous voltages of different PV modules in the faulty strings. Experimental results show that the proposed method can successfully detect and locate faulty strings and modules in several faulty cases, including the line-line faults, the degradation faults, the partial shading faults ... F C Han, Z C Chen, L J Wu, J L Yu, C Long, P J Lin, S Y Cheng and F P Su Institute of Physics (IOP) 1755-1307 17551307 1755-1315 17551315 |
shingle_catch_all_4 | Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier This paper presents a novel fault detection method for photovoltaic (PV) array using an improved two-stage Hampel identifier, which can quickly detect the occurrence of faults and locate them at PV module level. The fault detection method is implemented in a two-level wireless sensor network based distributed on-line monitoring system which is developed to monitor the voltage of each PV module and current of all parallel PV strings in real-time. The 1 st stage Hampel identifier detects and locates the faulty PV strings by comparing the instantaneous currents of different PV strings. The 2 nd stage Hampel identifier detects and locates the faulty PV modules by comparing the instantaneous voltages of different PV modules in the faulty strings. Experimental results show that the proposed method can successfully detect and locate faulty strings and modules in several faulty cases, including the line-line faults, the degradation faults, the partial shading faults ... F C Han, Z C Chen, L J Wu, J L Yu, C Long, P J Lin, S Y Cheng and F P Su Institute of Physics (IOP) 1755-1307 17551307 1755-1315 17551315 |
shingle_title_1 | Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier |
shingle_title_2 | Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier |
shingle_title_3 | Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier |
shingle_title_4 | Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier |
timestamp | 2025-06-30T23:37:13.286Z |
titel | Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier |
titel_suche | Online module-level fault detection of PV arrays using an improved two-stage Hampel identifier |
topic | R TE-TZ U |
uid | ipn_articles_6350435 |