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Experimental assessment of long-term performance degradation for a PV power plant operating in a desert maritime climate

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  • Hassan Daher, Daha
  • Gaillard, Léon
  • Ménézo, Christophe

Abstract

Photovoltaic (PV) installations are being intensively deployed and their capacity are approaching to terawatt around the world. In this context, the long-term performance and reliability of PV modules, component and systems are critical metrics for the economic viability of PV power plants. Furthermore, this is linked to the environmental conditions in which the PV plants operate. In this study, the performance degradation of a 302.4 kWp solar PV power plant is investigated over the first five years of operation in the desert maritime climate of Djibouti. The analysis is led on collected data extracted from the PV installation and that have been pre-processed and filtered. For this purpose, several criteria have been introduced to identify anomalies such as grid outages. Then, the power degradation rate was considered using Photovoltaics for Utility Scale Applications (PVUSA) regression analysis and Performance Ratio (PR) analysis based on continuous monitoring data at 1-min intervals. The degradation rates were found to be 1.01 ± 0.38%/year for PR and 0.085 ± 0.68%/year for PVUSA. According that the PVUSA did not detect any degradation, new test conditions that were set by experimental data have been introduced. Finally, the resulting measure allowed a degradation rate of 0.74 ± 0.29%/year to be observed.

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  • Hassan Daher, Daha & Gaillard, Léon & Ménézo, Christophe, 2022. "Experimental assessment of long-term performance degradation for a PV power plant operating in a desert maritime climate," Renewable Energy, Elsevier, vol. 187(C), pages 44-55.
    • Handle: RePEc:eee:renene:v:187:y:2022:i:c:p:44-55
    DOI: 10.1016/j.renene.2022.01.056
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    6. Karttunen, Lauri & Jouttijärvi, Sami & Poskela, Aapo & Palonen, Heikki & Huerta, Hugo & Todorović, Milica & Ranta, Samuli & Miettunen, Kati, 2023. "Comparing methods for the long-term performance assessment of bifacial photovoltaic modules in Nordic conditions," Renewable Energy, Elsevier, vol. 219(P1).
    7. Boccalatte, Alessia & Thebault, Martin & Paolini, Riccardo & Fossa, Marco & Ramousse, Julien & Ménézo, Christophe & Santamouris, Mattheos, 2023. "Assessing the combined effects of local climate and mounting configuration on the electrical and thermal performance of photovoltaic systems. Application to the greater Sydney area," Renewable Energy, Elsevier, vol. 219(P1).
    8. Masoud Emamian & Aref Eskandari & Mohammadreza Aghaei & Amir Nedaei & Amirmohammad Moradi Sizkouhi & Jafar Milimonfared, 2022. "Cloud Computing and IoT Based Intelligent Monitoring System for Photovoltaic Plants Using Machine Learning Techniques," Energies, MDPI, vol. 15(9), pages 1-25, April.

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