Khalifa University PhD Student’s Paper Applies Principles from Wind Energy Industry to Review PV System Operation and Maintenance
A team of researchers from Khalifa University have recommended advancing maintenance practices for large-scale photovoltaic (PV) systems by implementing comprehensive system-wide strategies and optimizing scheduling, potentially resulting in annual cost savings of up to US$10,000 per megawatt (MW).
The paper, ‘Photovoltaic Systems Operation and Maintenance: A Review and Future Directions’, published in the Top 5% journal Renewable and Sustainable Energy Reviews by Elsevier, offers a fresh approach to studying the maintenance of photovoltaic (PV) systems. Khalifa University PhD student Hind Abdulla is the first author, with Dr. Andrei Sleptchenko, Associate Professor, Management Science and Engineering, as the main advisor, and Dr. Ammar Nayfeh, Associate Professor, Electrical Engineering, the co-advisor.
The expansion of complex large-scale systems and the absence of established maintenance strategies for diverse portfolios are the reason for current challenges. In response, the researchers advocate for integrating adaptive techniques such as reinforcement learning to enhance system-wide reliability, efficiency, and sustainability. This approach is aimed at ensuring the continuous relevance of performance metrics in PV operation and maintenance (O&M).
The research finds that despite the simplicity of their design, maintenance tasks of PV systems are more challenging. In fact, studies show that implementing effective O&M strategies can recover an average energy gain of 5.27% for a typical 16.1 MWp PV plant, translating to an annual cost savings of US$10,000 per MW. Without effective O&M strategies, the global PV industry could face an alarming annual loss of US$14.5 billion in 2024 alone. In light of these concerns, the main objective of this review is to comprehensively examine the development of PV O&M over the past decade and systematically analyze key topics and their interconnections within the field.
Using a specific method called the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, the study categorized the research into four main areas: strategies to maintain the PV systems, measuring their performance; how they deteriorate over time and planning and optimizing maintenance activities for maximum efficiency.
Drawing insights from advanced maintenance approaches evident in the wind energy industry, this paper has found that proactive maintenance and data-driven decision-making are crucial in ensuring the optimal performance of solar systems. Unlike previous reviews, this research focuses on diverse maintenance elements while also incorporating planning and organizational factors into the discussion.
Key suggestions include employing adaptive methodologies such as reinforcement learning to tailor metrics for large-scale solar installations and effectively streamline the long-term maintenance of PV systems. The paper additionally suggests implementing dynamic protocols, departing from traditional static approaches that focus solely on individual components. Instead, it suggests taking a system-wide perspective and utilizing machine learning to prioritize potential risks in PV systems.
Dr. Sleptchenko said: “Innovation in sustainability is key at Khalifa University and to achieve a sustainable energy landscape, we recognize the crucial roles of wind and solar energy including through PV, in the overall energy system. Maintenance of PV systems extends beyond addressing technical issues, including strategic allocation of resources, prioritization of tasks, and formulation of contingency plans. Our paper found that a majority of existing research has focused primarily on individual aspects of O&M, neglecting the integration of crucial elements such as human resources, inventory, transportation, and supply network management. Understanding the interconnections between these aspects is essential for optimizing maintenance and making well-informed decisions.
He added: “In addition, our review sets the stage for integrating innovative strategies in future PV O&M efforts, showcasing the importance of the new Maintenance 5.0 paradigm in renewable energy production. These strategies combine advanced technologies and human expertise to improve performance, optimize operations, and foster a sustainable energy landscape through collaborative human-centric approaches.”
Recognizing the critical role of maintenance in ensuring optimal performance, the study further identifies gaps and proposes avenues for improvement, recommending a shift towards predictive maintenance in PV systems. Furthermore, the findings from this paper also align with the UN Sustainable Development Goal 7 (SDG-7) to ‘ensure access to affordable, reliable, sustainable and modern energy for all’, while also ensuring grid security.
Alisha Roy
Science Writer
5 April 2024
