Fault Diagnosis Method Based on An Improved KNN Algorithm for PV strings

Lina Wang; Hongcheng Qiu; Pu Yang; Jihong Gao

doi:10.1109/ACEEE51855.2021.9575060

Fault Diagnosis Method Based on An Improved KNN Algorithm for PV strings

Lina Wang
, Hongcheng Qiu
, Pu Yang
, Jihong Gao

自动化科学与电气工程学院

Beihang University
Ltd.

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

5 引用（Scopus）

摘要

Rapid and accurate fault diagnosis under limited data has become one of the most important abilities of photovoltaic (PV) power generation systems. This study proposes an improved K-Nearest-Neighbor(KNN) method, which is based on the current at the maximum power point, voltage at the maximum power point and weather data. By using this method, short circuit, open circuit and shading of a PV string can be diagnosed quickly based on data obtained by inverters and weather monitor. Finally, a large number of data was obtained through a credible model whose data is proved to be consistent with the measured data greatly. Diagnosis result of the method was evaluated through these data.

源语言	英语
主期刊名	2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021
出版商	Institute of Electrical and Electronics Engineers Inc.
页	91-98
页数	8
ISBN（电子版）	9781665418959
DOI	https://doi.org/10.1109/ACEEE51855.2021.9575060
出版状态	已出版 - 10 9月 2021
活动	4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021 - Virtual, Bangkok, 泰国期限: 10 9月 2021 → 12 9月 2021

出版系列

姓名	2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021

会议

会议	4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021
国家/地区	泰国
市	Virtual, Bangkok
时期	10/09/21 → 12/09/21

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 7 经济适用的清洁能源

访问文件

10.1109/ACEEE51855.2021.9575060

其它文件与链接

链接到 Scopus 的出版物

引用此

Wang, L., Qiu, H., Yang, P., & Gao, J. (2021). Fault Diagnosis Method Based on An Improved KNN Algorithm for PV strings. 在 2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021 (页码 91-98). (2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACEEE51855.2021.9575060

@inproceedings{3c3b3b06a89f4a42ba64992adab75cb6,

title = "Fault Diagnosis Method Based on An Improved KNN Algorithm for PV strings",

abstract = "Rapid and accurate fault diagnosis under limited data has become one of the most important abilities of photovoltaic (PV) power generation systems. This study proposes an improved K-Nearest-Neighbor(KNN) method, which is based on the current at the maximum power point, voltage at the maximum power point and weather data. By using this method, short circuit, open circuit and shading of a PV string can be diagnosed quickly based on data obtained by inverters and weather monitor. Finally, a large number of data was obtained through a credible model whose data is proved to be consistent with the measured data greatly. Diagnosis result of the method was evaluated through these data.",

keywords = "Fault diagnosis, K-Nearest-Neighbor, Photovoltaic, PV model, PV string",

author = "Lina Wang and Hongcheng Qiu and Pu Yang and Jihong Gao",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021 ; Conference date: 10-09-2021 Through 12-09-2021",

year = "2021",

month = sep,

day = "10",

doi = "10.1109/ACEEE51855.2021.9575060",

language = "英语",

series = "2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "91--98",

booktitle = "2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021",

address = "美国",

}

Wang, L, Qiu, H, Yang, P & Gao, J 2021, Fault Diagnosis Method Based on An Improved KNN Algorithm for PV strings. 在 2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021. 2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021, Institute of Electrical and Electronics Engineers Inc., 页码 91-98, 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021, Virtual, Bangkok, 泰国, 10/09/21. https://doi.org/10.1109/ACEEE51855.2021.9575060

Fault Diagnosis Method Based on An Improved KNN Algorithm for PV strings. / Wang, Lina; Qiu, Hongcheng; Yang, Pu 等.
2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021. Institute of Electrical and Electronics Engineers Inc., 2021. 页码 91-98 (2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Fault Diagnosis Method Based on An Improved KNN Algorithm for PV strings

AU - Wang, Lina

AU - Qiu, Hongcheng

AU - Yang, Pu

AU - Gao, Jihong

PY - 2021/9/10

Y1 - 2021/9/10

N2 - Rapid and accurate fault diagnosis under limited data has become one of the most important abilities of photovoltaic (PV) power generation systems. This study proposes an improved K-Nearest-Neighbor(KNN) method, which is based on the current at the maximum power point, voltage at the maximum power point and weather data. By using this method, short circuit, open circuit and shading of a PV string can be diagnosed quickly based on data obtained by inverters and weather monitor. Finally, a large number of data was obtained through a credible model whose data is proved to be consistent with the measured data greatly. Diagnosis result of the method was evaluated through these data.

AB - Rapid and accurate fault diagnosis under limited data has become one of the most important abilities of photovoltaic (PV) power generation systems. This study proposes an improved K-Nearest-Neighbor(KNN) method, which is based on the current at the maximum power point, voltage at the maximum power point and weather data. By using this method, short circuit, open circuit and shading of a PV string can be diagnosed quickly based on data obtained by inverters and weather monitor. Finally, a large number of data was obtained through a credible model whose data is proved to be consistent with the measured data greatly. Diagnosis result of the method was evaluated through these data.

KW - Fault diagnosis

KW - K-Nearest-Neighbor

KW - Photovoltaic

KW - PV model

KW - PV string

UR - https://www.scopus.com/pages/publications/85119293976

U2 - 10.1109/ACEEE51855.2021.9575060

DO - 10.1109/ACEEE51855.2021.9575060

M3 - 会议稿件

AN - SCOPUS:85119293976

T3 - 2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021

SP - 91

EP - 98

BT - 2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021

Y2 - 10 September 2021 through 12 September 2021

ER -

Wang L, Qiu H, Yang P, Gao J. Fault Diagnosis Method Based on An Improved KNN Algorithm for PV strings. 在 2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021. Institute of Electrical and Electronics Engineers Inc. 2021. 页码 91-98. (2021 4th Asia Conference on Energy and Electrical Engineering, ACEEE 2021). doi: 10.1109/ACEEE51855.2021.9575060

Fault Diagnosis Method Based on An Improved KNN Algorithm for PV strings

摘要

出版系列

会议

联合国可持续发展目标

访问文件

其它文件与链接

学术指纹

引用此