I-V Curve Differences Image Classification by CNN for Failure Factor Determination in PV system

Shunya Hasegawa, Yuzuru Ueda

研究成果: Conference contribution査読

2 被引用数 (Scopus)

抄録

With a widespread of photovoltaic (PV) systems, a long-term use of the systems is expected. Since the amount of power generation can be decreased due to failures by various causes in the system, a practical way to detect the cause of the failure is needed for long-term uses of the system. This paper proposes a method to determine the cause of the failure in the PV system using convolutional neural network (CNN) by classifying the image of measured I-V curves which might have some failures. As a result, a case of the I-V curves which were caused by a stepped defect in a string unit was detected 100% correctly.

本文言語English
ホスト出版物のタイトル2020 47th IEEE Photovoltaic Specialists Conference, PVSC 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ683-688
ページ数6
ISBN(電子版)9781728161150
DOI
出版ステータスPublished - 14 6月 2020
イベント47th IEEE Photovoltaic Specialists Conference, PVSC 2020 - Calgary, Canada
継続期間: 15 6月 202021 8月 2020

出版物シリーズ

名前Conference Record of the IEEE Photovoltaic Specialists Conference
2020-June
ISSN(印刷版)0160-8371

Conference

Conference47th IEEE Photovoltaic Specialists Conference, PVSC 2020
国/地域Canada
CityCalgary
Period15/06/2021/08/20

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