2 publications
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Published Subscription
Detailed survey on detection of Dirtiness of PV panels using different approachesBy Khushalchand S. Sharma, Shrikant Chavate
Abstract: The accumulation of dust, dirt, bird droppings, pollen, and other environmental contaminants on photovoltaic (PV) panels significantly reduces their power generation efficiency and increases operational and maintenance costs. Therefore, timely and accurate detection of the cleanliness condition of solar panels is essential for maintaining optimal energy production, improving system reliability, and extending the operational lifespan of PV installations. In recent years, considerable research interest has been directed toward automated soiling …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article →
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Published Subscription
An approach for Intelligent detection of dirty PV panels using image processing with YOLOv8By Khushalchand S. Sharma, Shrikant Chavate
Abstract: The efficiency of solar photovoltaic (PV) systems is greatly affected by the condition of panel surfaces, as dust buildup and other impurities can noticeably reduce power output. Traditional maintenance methods rely largely on manual inspection, which can be subjective, inconsistent, and impractical for large-scale installations. To address these challenges, this work investigates a deep learning-based computer vision approach for the automatic assessment of solar panel cleanliness. In this work, a …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 12, Issue 2, 2026 Read article →