An early fault detection approach in grid-connected photovoltaic (GCPV) system

Faults in any components of PV system shall lead to performance degradation and if prolonged, it can leads to fire hazard. This paper presents an approach of early fault detection via acquired historical data sets of grid-connected PV (GCPV) systems. The approach is a developed algorithm comprises o...

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書誌詳細
出版年:Indonesian Journal of Electrical Engineering and Computer Science
第一著者: 2-s2.0-85074153917
フォーマット: 論文
言語:English
出版事項: Institute of Advanced Engineering and Science 2019
オンライン・アクセス:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074153917&doi=10.11591%2fijeecs.v17.i2.pp671-679&partnerID=40&md5=34e5c70bf1a00e17527421c98c6f5a76
id Muhammad N.; Zainuddin H.; Jaaper E.; Idrus Z.
spelling Muhammad N.; Zainuddin H.; Jaaper E.; Idrus Z.
2-s2.0-85074153917
An early fault detection approach in grid-connected photovoltaic (GCPV) system
2019
Indonesian Journal of Electrical Engineering and Computer Science
17
2
10.11591/ijeecs.v17.i2.pp671-679
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074153917&doi=10.11591%2fijeecs.v17.i2.pp671-679&partnerID=40&md5=34e5c70bf1a00e17527421c98c6f5a76
Faults in any components of PV system shall lead to performance degradation and if prolonged, it can leads to fire hazard. This paper presents an approach of early fault detection via acquired historical data sets of grid-connected PV (GCPV) systems. The approach is a developed algorithm comprises of failure detection on AC power by using Acceptance Ratio (AR) determination. Specifically, the implemented failure detection stage was based on the algorithm that detected differences between the actual and predicted AC power of PV system. Furthermore, the identified alarm of system failure was a decision stage which performed a process based on developed logic and decision trees. The results obtained by comparing two types of GCPV system (polycrystalline and monocrystalline silicon PV system), showed that the developed algorithm could perceive the early faults upon their occurrence. Finally, when applying AR to the PV systems, the faulty PV system demonstrated 93.38% of AR below 0.9, while the fault free PV system showed only 31.4% of AR below 0.9. Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved.
Institute of Advanced Engineering and Science
25024752
English
Article
All Open Access; Gold Open Access; Green Open Access
author 2-s2.0-85074153917
spellingShingle 2-s2.0-85074153917
An early fault detection approach in grid-connected photovoltaic (GCPV) system
author_facet 2-s2.0-85074153917
author_sort 2-s2.0-85074153917
title An early fault detection approach in grid-connected photovoltaic (GCPV) system
title_short An early fault detection approach in grid-connected photovoltaic (GCPV) system
title_full An early fault detection approach in grid-connected photovoltaic (GCPV) system
title_fullStr An early fault detection approach in grid-connected photovoltaic (GCPV) system
title_full_unstemmed An early fault detection approach in grid-connected photovoltaic (GCPV) system
title_sort An early fault detection approach in grid-connected photovoltaic (GCPV) system
publishDate 2019
container_title Indonesian Journal of Electrical Engineering and Computer Science
container_volume 17
container_issue 2
doi_str_mv 10.11591/ijeecs.v17.i2.pp671-679
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074153917&doi=10.11591%2fijeecs.v17.i2.pp671-679&partnerID=40&md5=34e5c70bf1a00e17527421c98c6f5a76
description Faults in any components of PV system shall lead to performance degradation and if prolonged, it can leads to fire hazard. This paper presents an approach of early fault detection via acquired historical data sets of grid-connected PV (GCPV) systems. The approach is a developed algorithm comprises of failure detection on AC power by using Acceptance Ratio (AR) determination. Specifically, the implemented failure detection stage was based on the algorithm that detected differences between the actual and predicted AC power of PV system. Furthermore, the identified alarm of system failure was a decision stage which performed a process based on developed logic and decision trees. The results obtained by comparing two types of GCPV system (polycrystalline and monocrystalline silicon PV system), showed that the developed algorithm could perceive the early faults upon their occurrence. Finally, when applying AR to the PV systems, the faulty PV system demonstrated 93.38% of AR below 0.9, while the fault free PV system showed only 31.4% of AR below 0.9. Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved.
publisher Institute of Advanced Engineering and Science
issn 25024752
language English
format Article
accesstype All Open Access; Gold Open Access; Green Open Access
record_format scopus
collection Scopus
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