RESEARCH ON FAULT DIAGNOSIS OF PHOTOVOLTAIC ARRAY BASED ON VMD-CNN-BiLSTM OPTIMIZED BY IMPROVED SPARROW SEARCH ALGORITHM

Yu Yang; Guo Dong; Xu Yi; Wang Pengwei; Gao Chao; Sui Yongjia

doi:10.19912/j.0254-0096.tynxb.2024-2338

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (5) : 627-638. DOI: 10.19912/j.0254-0096.tynxb.2024-2338

RESEARCH ON FAULT DIAGNOSIS OF PHOTOVOLTAIC ARRAY BASED ON VMD-CNN-BiLSTM OPTIMIZED BY IMPROVED SPARROW SEARCH ALGORITHM

Yu Yang, Guo Dong, Xu Yi, Wang Pengwei, Gao Chao, Sui Yongjia

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Abstract

To address the challenges in precise fault identification and diagnostic reliability enhancement for photovoltaic （PV） arrays, this study develops an integrated fault diagnosis framework incorporating Adaptive Sparrow Search Algorithm （ASFSSA）-optimized Variational Mode Decomposition （VMD） with a hybrid Convolutional Neural Network-Bidirectional Long Short-Term Memory （CNN-BiLSTM） architecture. The framework comprises three principal phases： Initially, ASFSSA-driven parameter optimization is implemented for VMD's critical parameters （modal components K and penalty coefficient α）, enhancing computational efficiency and decomposition precision. Subsequently, the optimized VMD algorithm performs multiscale decomposition of PV array fault signals to selectively extract discriminative feature components. Ultimately, these processed features are fed into the CNN-BiLSTM network for hierarchical feature abstraction and multi-class fault pattern recognition. Comprehensive experimental evaluations demonstrate the framework's superior performance, achieving 98.97% mean diagnostic accuracy on benchmark datasets and 99.30% accuracy on operational PV plant fault data, surpassing benchmark models in both controlled and real-world scenarios. These quantitative outcomes substantiate the technical viability and diagnostic effectiveness of the proposed intelligent fault diagnosis system.

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failure analysis / photovoltaic array / convolutional neural networks / long short-term memory / variational mode decomposition / sparrow search algorithm

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Yu Yang, Guo Dong, Xu Yi, Wang Pengwei, Gao Chao, Sui Yongjia. RESEARCH ON FAULT DIAGNOSIS OF PHOTOVOLTAIC ARRAY BASED ON VMD-CNN-BiLSTM OPTIMIZED BY IMPROVED SPARROW SEARCH ALGORITHM[J]. Acta Energiae Solaris Sinica. 2026, 47(5): 627-638 https://doi.org/10.19912/j.0254-0096.tynxb.2024-2338

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