Abstract
Solar panels' power output is greatly impacted by environmental factors such as weather patterns and air pollution. A solar panel's ability to generate power is limited by unfavorable weather conditions and pollution in the air. To ensure that solar panels are installed correctly and perform optimally, it is particularly important to understand their power output prior to their installation. A method for predicting solar panel power output is presented in this paper based on weather and air pollution characteristics. In order to develop machine learning models, three types of features are taken into account, including the weather, air pollution, and the combination of the two. The data was collected from the Gulf Countries (Saudi Arabia, the United Arab Emirates, Kuwait, Bahrain, Qatar and Oman) between 2018 and 2020. Experiments conducted on solar panels indicate that weather and air pollution can be decisive factors in predicting power output.
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