Photovoltaic Modules’ Cleaning Method Selection for the MENA Region
Haneen Abuzaid (),
Mahmoud Awad and
Abdulrahim Shamayleh
Additional contact information
Haneen Abuzaid: Department of Industrial Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates
Mahmoud Awad: Department of Industrial Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates
Abdulrahim Shamayleh: Department of Industrial Engineering, American University of Sharjah, Sharjah P.O. Box 26666, United Arab Emirates
Sustainability, 2024, vol. 16, issue 21, 1-23
Abstract:
Photovoltaic (PV) systems are important components of the global shift towards sustainable energy resources, utilizing solar energy to generate electricity. However, the efficiency and performance of PV systems heavily rely on cleanliness, as dust accumulation can significantly obstruct their effectiveness over time. This study undertook a comprehensive literature review and carried out multiple interviews with experts in the PV systems field to propose a map for selecting the optimal PV cleaning method for PV systems within MENA region. These factors, covering meteorological conditions, the local environment, PV system design, module characteristics, dust deposition attributes, exposure time to dust, and socio-economic and environmental considerations, were employed as criteria in a Multi-Criteria Decision-Making (MCDM) model, specifically, an Analytic Network Process (ANP). The results indicate that partially automated cleaning is the most suitable method for existing utility-scale PV projects in the MENA region. The findings provide robust guidelines for PV system stakeholders, aiding informed decision-making and enhancing the sustainability of PV cleaning processes.
Keywords: photovoltaic (PV) systems; maintenance or PV cleaning methods; Multi-Criteria Decision-Making (MCDM) model; Analytic Network Process (ANP) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:21:p:9331-:d:1507764
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