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Optimizing cleaning schedules for spatially distributed photovoltaic installations with site-specific variations

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  • Abdulla, Hind
  • Sleptchenko, Andrei
  • Nayfeh, Ammar

Abstract

The rapid growth of photovoltaic (PV) installations has led to the deployment of dispersed PV fleets across diverse locations. Effective operation and maintenance (O&M), particularly proactive cleaning, is critical to mitigate soiling, which significantly impacts system performance. Standard cleaning strategies tailored to individual sites are challenging to scale across multi-system fleets due to site-specific variations, resulting in high costs and operational complexities. This paper introduces a mixed-integer linear programming model to optimize cleaning schedules for dispersed PV systems. The model accounts for site-specific factors such as soiling losses, cleaning costs, and generation capacities, dynamically adjusting cleaning frequencies to enhance fleet-wide performance and profitability. Results highlight the benefits of tailored scheduling, with some sites requiring more frequent cleaning while all contribute to overall profitability, validating the fleet-wide approach. Computational experiments show substantial profit gains, with dynamic scheduling achieving a 15–34% profit increase compared to interval-based scheduling and a 2–5% improvement over threshold-based approaches. By aligning resource use with site-specific conditions, this approach supports renewable energy goals by stabilizing production and minimizing environmental impact. The framework provides a robust, cost-effective solution for O&M contractors to optimize PV operations and promote sustainability, with potential for real-time enhancements to adapt to evolving conditions.

Suggested Citation

  • Abdulla, Hind & Sleptchenko, Andrei & Nayfeh, Ammar, 2025. "Optimizing cleaning schedules for spatially distributed photovoltaic installations with site-specific variations," Renewable Energy, Elsevier, vol. 248(C).
    • Handle: RePEc:eee:renene:v:248:y:2025:i:c:s0960148125006330
    DOI: 10.1016/j.renene.2025.122971
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    References listed on IDEAS

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