Solar PV Forecasting Using Machine Learning Models
Mellempudi Nikitha, K C R Nisha, M Santhosh Gowda, Pramod Aithal, Nehna Manoj Mudakkayil
Abstract
Renewable energy is increasingly being used to mitigate the consequences of climate change and global warming. Various prediction strategies have been developed in attempt to increase renewable energy prediction ability. Solar Forecasting is an important procedure in PV systems to minimise safety and stability issues caused by its nature. The following are the objectives of this study, to give a quick overview of the various solar PV forecasting approaches. The significance of machine learning in forecasting is discussed, as well as the procedures required. This work aims to provide a review and evaluation of ML models used to forecast solar energy. It illustrates processes used in ML models for solar energy forecasts, such as data pre-processing approaches and parameter selection algorithms.