Solar power forecasting using a hybrid EMD-ELM method

In present scenario the energy system face various challenges as the demand for energy is increasing significantly and the resources in terms of fossil fuels are limited, need for renewable resources have became very much vital at present. Accurate and reliable solar power forecasting is essential for the legitimate functioning of the power system. Given momentous uncertainties involved in solar power generation due to variation of temperature and irradiance, forecasting provides a unique solution for the uncertainties and variability's in solar data. In this paper a forecasting method has been mentioned that is contingent on a hybrid empirical mode decomposition (EMD) and Extreme Learning Machine (ELM). The non stationary time series is further decomposed into distinct intrinsic mode functions (IMF). A short term forecasting is also carried out in this work to prove the accuracy of the given model. This model is implemented in MATLAB/SCRIPT environment.