A Two-Stage Wiener Degradation Model-Based Approach for Visual Maintenance of Photovoltaic Modules

This study proposes a novel visual maintenance method for photovoltaic (PV) modules based on a two-stage Wiener degradation model, addressing the limitations of traditional PV maintenance strategies that often result in insufficient or excessive maintenance. The approach begins by constructing a two-stage Wiener process performance degradation model and a remaining life prediction model under perfect maintenance conditions using historical degradation data of PV modules. This enables accurate determination of the optimal timing for post-failure corrective maintenance. To optimize the maintenance strategy, the study establishes a comprehensive cost model aimed at minimizing the long-term average cost rate. The model considers multiple cost factors, including inspection costs, preventive maintenance costs, restorative maintenance costs, and penalty costs associated with delayed fault detection. Through this optimization framework, the method determines both the optimal maintenance threshold and the ideal timing for predictive maintenance actions. Comparative analysis demonstrates that the two-stage Wiener model provides superior fitting performance compared to conventional linear and nonlinear degradation models. When evaluated against traditional maintenance approaches, including Wiener process-based corrective maintenance strategies and static periodic maintenance strategies, the proposed method demonstrates significant advantages in reducing overall operational costs while extending the effective service life of PV components. The method achieves these improvements through effective coordination between reliability optimization and economic benefit maximization, leading to enhanced power generation performance. These results indicate that the proposed approach offers a more balanced and efficient solution for PV system maintenance.