电源学报

基于IDBO-LightGBM的光伏阵列故障诊断方法

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吴亚钧 , 王璐 , 张金江中国电源学会会员

电源学报 | 新能源发电与储能 2026,24(4): 122-132

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电源学报 |新能源发电与储能 2026 , 24 (4) : 122 -132

基于IDBO-LightGBM的光伏阵列故障诊断方法

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吴亚钧（2000—　），男，硕士研究生。研究方向：光伏发电故障诊断技术。E-mail：222207855020@zust.edu.cn。

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吴亚钧（2000—　），男，硕士研究生。研究方向：光伏发电故障诊断技术。E-mail：222207855020@zust.edu.cn。

王璐（1999—　），男，硕士研究生。研究方向：微电网能源调度。E-mail：222107855029@zust.edu.cn。

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王璐（1999—　），男，硕士研究生。研究方向：微电网能源调度。E-mail：222107855029@zust.edu.cn。

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吴亚钧, 王璐, 张金江中国电源学会会员

作者信息

浙江科技大学自动化与电气工程学院，杭州　310023

通讯作者:

张金江（1971—　），男，中国电源学会会员，通信作者，博士，副教授。研究方向：智能电网风险评估与运行控制。E-mail：jjzhang@zust.edu.cn。

作者简介:

吴亚钧（2000—　），男，硕士研究生。研究方向：光伏发电故障诊断技术。E-mail：222207855020@zust.edu.cn。

王璐（1999—　），男，硕士研究生。研究方向：微电网能源调度。E-mail：222107855029@zust.edu.cn。

Fault Diagnosis Method for Photovoltaic Arrays Based on IDBO-LightGBM

Yajun WU, Lu WANG, Jinjiang ZHANG Member, CPSS

Affiliations

School of Automation and Electrical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China

出版时间: 2026-04-30 doi: 10.13234/j.issn.2095-2805.2026.4.122

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摘要

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为提高光伏阵列故障诊断的准确率，提出1种基于改进蜣螂优化IDBO（improved dung beetle optimazation）算法优化轻量级梯度提升机LightGBM（light gradient boosting machine）的光伏阵列故障诊断方法。通过IDBO对LightGBM中的特定超参数进行寻优，建立基于IDBO-LightGBM的光伏阵列故障诊断模型。为有效区分各种故障，使用从电流-电压曲线中提取的特征点。为验证所提方法的效果，对模型进行仿真分析，将所提方法与LightGBM算法、DBO-LightGBM算法、其他决策树算法和支持向量机算法进行对比，验证了所提方法的稳定性与准确率。

关键词

光伏阵列 / 故障诊断 / 改进蜣螂优化算法 / 轻量级梯度提升机

Abstract

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To improve the accuracy of fault diagnosis for photovoltaic arrays, a photovoltaic fault diagnosis method based on an improved dung beetle optimization (IDBO) algorithm which is used to optimize a light gradient boosting machine (LightGBM) is proposed. The IDBO algorithm is used to optimize specific hyperparameters in LightGBM, and a fault diagnosis model for photovoltaic arrays based on IDBO-LightGBM is established. To effectively distinguish various faults, the characteristic points extracted from the current-voltage curves are utilized. To validate the effectiveness of the proposed method, simulation analysis is conducted on the model. A comparison is performed among the proposed method, LightGBM algorithm, DBO-LightGBM algorithm, other decision tree algorithms and support vector machine algorithm, and results verify the stability and accuracy of the novel method.

Key words

Photovoltaic array / fault diagnosis / improved dung beetle optimization (IDBO) algorithm / light gradient boosting machine (LightGBM)

引用本文

吴亚钧, 王璐, 张金江中国电源学会会员. 基于IDBO-LightGBM的光伏阵列故障诊断方法. 电源学报, 2026 , 24 (4) : 122 -132 . DOI: 10.13234/j.issn.2095-2805.2026.4.122

Yajun WU, Lu WANG, Jinjiang ZHANG. Fault Diagnosis Method for Photovoltaic Arrays Based on IDBO-LightGBM[J]. Journal of Power Supply, 2026 , 24 (4) : 122 -132 . DOI: 10.13234/j.issn.2095-2805.2026.4.122

基金

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浙江省“尖兵”“领雁”研发攻关计划资助项目(2025C01149)

参考文献

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2026年第24卷第4期

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文章信息

doi: 10.13234/j.issn.2095-2805.2026.4.122

接收时间：2023-11-02
首发时间：2026-10-29
出版时间：2026-04-30

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出版历史

收稿日期：2023-11-02
修回日期：2023-12-18
录用日期：2023-12-22

基金

“Pioneer” and “Leading Goose” R&D Program of Zhejiang(2025C01149)

浙江省“尖兵”“领雁”研发攻关计划资助项目(2025C01149)

作者信息

浙江科技大学自动化与电气工程学院，杭州　310023

通讯作者:

张金江（1971—　），男，中国电源学会会员，通信作者，博士，副教授。研究方向：智能电网风险评估与运行控制。E-mail：jjzhang@zust.edu.cn。

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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