Development of Near-Real-Time Solar Generation Prediction Technique Using Weather Data

This paper presents a technique for forecasting solar power generation using weather forecast data. Solar power generation mainly depends on the relative position of the sun and some extrinsic as well as intrinsic factors. Extrinsic factors, such as cloud cover, temperature, rainfall, humidity, and wind speed, are used for the prediction of solar generation. Apart from these, the intrinsic factors are also taken as inputs for the proposed prediction technique. The artificial intelligence–based techniques of linear regression, polynomial regression, and artificial neural networks are used for prediction purposes, with input data of all the months of the year 2021. After developing different AI models, their accuracies are compared before selecting the best technique for solar generation prediction. The AI model found to be accurate during the present work is applicable to all solar generation systems, for generation level prediction.