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An experimental comparative analysis of different PV technologies performance including the influence of hot-arid climatic parameters: Toward a realistic yield assessment for desert locations

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  • Mehdi, Maryam
  • Ammari, Nabil
  • Alami Merrouni, Ahmed
  • El Gallassi, Hicham
  • Dahmani, Mohamed
  • Ghennioui, Abdellatif

Abstract

In this study, a one-year experiment has been conducted to evaluate the performances of two different photovoltaic technologies: Polycrystalline (pc-Si) and cadmium telluride (CdTe) under a hot desert climate in Mid-south Morocco. For this reason, two PV modules (from each technology) have been exposed and all electrical parameters were monitored for performance comparison. Also, for a realistic comparison, the impact of the climatic parameters, mainly soiling and temperature were taken into consideration. Results show that both technologies have a good performance with a daily Performance Ratio (PR) close to 1 for the pc-Si and around 0.9 for CdTe, but with superiority of 3.5% to the pc-Si technology. The peak daily energy yields are of 7.51 kWh/kWp and 6.99 kWh/kWp for pc-Si and CdTe respectively, with 7% high production for the pc-Si. Nevertheless, the CdTe is less affected by temperature, where the average PR deviation (between the technologies) is 4.37% for temperature values less than 25 °C and 2.35% for temperatures above 25 °C in favor of the CdTe. Regarding soiling, the CdTe shows high performance in comparison to the pc-Si where the daily Soiling Rate reaches 24.6% and 26.9% for both technologies respectively, which causes a drop in the electricity production of 25.5% for the pc-Si and 23.2% for CdTe technology.

Suggested Citation

  • Mehdi, Maryam & Ammari, Nabil & Alami Merrouni, Ahmed & El Gallassi, Hicham & Dahmani, Mohamed & Ghennioui, Abdellatif, 2023. "An experimental comparative analysis of different PV technologies performance including the influence of hot-arid climatic parameters: Toward a realistic yield assessment for desert locations," Renewable Energy, Elsevier, vol. 205(C), pages 695-716.
    • Handle: RePEc:eee:renene:v:205:y:2023:i:c:p:695-716
    DOI: 10.1016/j.renene.2023.01.082
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    2. Tan, Hongjun & Guo, Zhiling & Chen, Yuntian & Zhang, Haoran & Song, Chenchen & Jiang, Mingkun & Yan, Jinyue, 2025. "PV potential analysis through deep learning and remote sensing-based urban land classification," Applied Energy, Elsevier, vol. 387(C).
    3. 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).
    4. Warsama, Aziza Idriss & Selimli, Selcuk, 2024. "Effect of dust deposition density and particle size on the energetic and exergetic performance of photovoltaic modules: An experimental study," Renewable Energy, Elsevier, vol. 226(C).

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