Effective Prediction of Solar Power Using Neural Network

Abstract

With climate change driving an increasingly secure influence over governments and municipalities, sustainable development, and renewable energy are gaining traction across the globe. In this sense, a tool that aids predicting the energy output of sustainable sources across the year for a particular location can aid greatly in making sustainable energy share more. Energy forecasting can be used to reduce some of the challenges that arise from the uncertainty in the resource. Solar power forecasting is observe a growing attention from the research community. The project presents an artificial neural network model to produce solar power forecasts. Sensitivity analysis of several input variables for best selection, and comparison of the model performance with multiple linear regression and resolve models are also shown.