Cost Effective Cleaning Optimization for Enhanced Solar PV Power Production in Arid Areas
Rahma AMAN, Amjad ALI, Kamran ALI, Farrukh BAIG, Muhammad Asghar KHAN, Sagheer Abbas
Abstract. Dust accumulation in arid environments results in energy losses associated with solar module performance and increases operational expenses. Real time operational and environmental data were used to evaluate the amount of soiling loss from 5 % to 20 % at the 300-megawatt Sakaka Solar Power Plant in Saudi Arabia between 2020 and 2024. Subsequently, the Grey Wolf Optimizer was employed to develop a method for determining the most effective cleaning schedule based on the balance between soiling related energy income losses and the associated cleaning expenses. An optimal annual cleaning frequency of 18 days with mechanized cleaning resulted in annual expenses of $0.37 million; while an optimal annual frequency of 45 days with manual cleaning resulted in annual expenses of $0.92 million. These frequencies are reduced to 15 and 37 days during the arid season. The proposed method provides a cost-effective means to support photovoltaic system maintenance using data, and is consistent with Saudi Arabia’s Vision 2030 renewable energy goals.
Keywords
Photovoltaic Systems, Soiling Losses, Cleaning Optimization, Grey Wolf Optimizer
Published online 4/25/2026, 9 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Rahma AMAN, Amjad ALI, Kamran ALI, Farrukh BAIG, Muhammad Asghar KHAN, Sagheer Abbas, Cost Effective Cleaning Optimization for Enhanced Solar PV Power Production in Arid Areas, Materials Research Proceedings, Vol. 64, pp 978-986, 2026
DOI: https://doi.org/10.21741/9781644904091-121
The article was published as article 121 of the book Energy Futures
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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