Sustainable strategies for preventive maintenance and replacement in photovoltaic power systems: Enhancing reliability, efficiency, and system economy

This study proposes a preventive maintenance and replacement strategy for photovoltaic (PV) power generation systems, addressing reliability as a key constraint. The research introduces a novel approach incorporating service age regression and failure rate increment factors to model PV equipment degradation. A flexible, non-periodic, and incomplete maintenance model is developed, optimizing maintenance cycles, pre-repair counts, and replacement schedules to balance maintenance costs and equipment availability. The model effectively mitigates the risks of over- or under-maintenance. Comparative analysis demonstrates that the proposed strategy, with an optimal maintenance setting of 0.913, reduces average maintenance costs by 21.4 % and 6.22 % while increasing equipment availability by 0.2411 % and 0.03222 %, compared to an equal-cycle maintenance model without reliability constraints and a model that disregards equipment replacement thresholds. These findings highlight the model's effectiveness in ensuring high operational reliability and economic efficiency of PV plants. The study contributes a novel optimization framework that enhances PV system sustainability by integrating reliability-driven maintenance and replacement decisions. However, it does not consider component correlations within PV systems. • Strategy for PV system maintenance ensures reliability and cost efficiency. • Flexible maintenance model reduces costs by 21.4 % and boosts availability by 0.2411 %. • Service age regression tracks PV equipment degradation for optimal repair. • Model prevents over/under-repair, improving operational reliability of PV plants.

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