Solar irradiance forecasting by using wavelet based denoising

Abstract

Predicting of global solar irradiance is very important in applications using solar energy resources. This research introduces a new methodology to estimate the solar irradiance. Denoising based on wavelet transformation as a preprocessing step is applied to the time series meteorological data. Artificial neural network and support vector machine are then used to make predictive model on Global Horizontal Irradiance (GHI) for the three cities located in California, Kentucky and New York, individually. Detailed experimental analysis is presented for the developed predictive models and comparisons with existing methodologies show that the proposed approach gives a significant improvement with increased generality.