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Predictive cleaning in solar farms, to maximize to energy production

Industry: Renewable energy
Site: Photovoltaic plant
Use Case: Prediction soiling panel
Region: Dubai – Middle East

Year: 2020



Solar farms can have several factors that influence the cleaning schedule, such as weather behavior, time of year, dirt, and other factors. Through this project, the objective is to evaluate the effect of these factors on the solar power plant, to generate a cleaning program that maximizes energy production, profits and avoids costs caused by unnecessary cleaning.



We developed a preventive and predictive maintenance, increasing production efficiency and reducing cost



The goal is to develop an artificial intelligence model to better know the degree of dirt on the panels, without the need for human intervention, and therefore optimize cleaning dates.



Create a cleaning program that maximizes energy production and profits and avoids unnecessary cleaning costs.

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