Novel clustering approach enhances performance evaluation in photovoltaic systems, indicating better condition monitoring and fault diagnosis.
Introduction: With the increasing integration of Photovoltaic (PV) systems, challenges in condition monitoring, fault diagnosis, and modeling of PV plants have intensified. Methodology: To address the cluster division aspect of these challenges, a novel and efficient method using an improved Spectral Clustering (SC) approach is proposed. The approach starts with preprocessing the PV data to normalize variations in magnitude. Results: The clustering process is then executed using the modified SC algorithm. To validate its effectiveness, comparative analyses are conducted using various clustering indices across different test cases. Discussion: To comprehensively evaluate the performance of the approach, a comprehensive index is proposed. Conclusion: The results confirm that the method significantly enhances the efficiency and speed of cluster division in large-scale PV plants, making it a promising tool for PV system management.
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Wang et al. (2026) studied this question.
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