Mechanisms and economics of a self-powered, automated, scalable solar PV surface cleaning system

Martin Paul Ndeto, Francis Njoka, David Wafula Wekesa and Robert Kinyua

Renewable Energy, 2024, vol. 226, issue C

Abstract: PV module exposure to ambient environmental factors, such as dust deposits, have negative effects on the module's peak power (Pmax) and overall power conversion efficiency (η). In this study the ideal counter-acting force needed to remove adhered dust particles on PV modules is investigated. An automated self-cleaning system that uses fluid velocities to suspend adhered dust particles on the PV module surface at a reduced induced static charge induction is designed. The automated system produces lift and drag forces of 3.973 N and 4.563 N per square metre, respectively, which are strong enough to loosen stuck-on dust particles on solar PV surfaces. The model's net present value (NPV) of $ 2383.71 with a dynamic payback period of 1.95 years and profitability index of 1.78 indicate that the investment in the self-cleaning model is financially feasible even for small-scale installations.

Keywords: Adhered dust deposits; Automated cleaning system; Net present value; Profitability index; PV performance (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:226:y:2024:i:c:s0960148124005421

DOI: 10.1016/j.renene.2024.120477

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