A review on application of Machine Learning in Solar Energy & Photovoltaic Generation Prediction
Sampurna Panda, Rakesh Kumar, Babita Panda, Arjyadhara Pradhan, Chitralekha Jena, Lipika Nanda
Abstract
As a supplement to traditional energy sources, solar energy is effective. Because of this, photovoltaic power grid (PVPG) is especially dependent on weather, and thus highly intermittent. Power systems depend on precise forecasting of photovoltaic power grid (PVPG) forms, which form the backbone of the generation, transmission, and distribution of electricity. Another challenge in managing photovoltaic systems is assuring both small and large-scale generation estimation. Thus chapter demonstrates the role of Artificial Intelligence in estimating solar energy generation. This paper also depicts the overview on importance of data pre-processing and parameter selection while applying machine learning for forecasting solar energy production.