Current Challenges in Operation, Performance, and Maintenance of Photovoltaic Panels

Tamás Orosz (), Anton Rassõlkin, Pedro Arsénio, Peter Poór, Daniil Valme and Ádám Sleisz
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Tamás Orosz: Department of Power Electronics and Electric Drives, Széchenyi István University of Győr, 9026 Győr, Hungary
Anton Rassõlkin: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia
Pedro Arsénio: E-REDES, Av. José Malhoa 25, 1070-157 Lisbon, Portugal
Peter Poór: Faculty of Management and Economics, Tomas Bata University, Mostní 5139, 760 01 Zlín, Czech Republic
Daniil Valme: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia
Ádám Sleisz: Department of Electric Power Engineering, Budapest University of Technology and Economics, Egry József Str. 18., 1111 Budapest, Hungary

Energies, 2024, vol. 17, issue 6, 1-22

Abstract: The installed solar capacity in the European Union has expanded rapidly in recent years. The production of these plants is stochastic and highly dependent on the weather. However, many factors should be considered together to estimate the expected output according to the weather forecast so that these new PV plants can operate at maximum capacity. Plants must be operated in coordination with maintenance operations and considering actual energy market prices. Various methods have recently been developed in the literature, ranging from the most impactful artificial-intelligence-based generation estimation methods to various diagnostic and maintenance methods. Moreover, the optimal operational and maintenance strategy usually depends on market regulation, and there are many concerns related to the distribution system operator. This review article aims to summarize and illustrate the challenges of operating and maintaining solar power plants and the economic and technical importance of these problems.

Keywords: photovoltaic; power generation; maintenance; ROI; artificial intelligence (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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