Enhancing the Accuracy in Renewable Energy Forecasting Using Improvised Deep Learning Techniques

Abstract

Renewable energies such as wind and solar begin receiving remarkable newlinepopularity in accordance with the energy demand, expeditious expansion of solar and wind newlineenergy generation involves acute forecasting of wind and solar power, so in past and recent newlineyears it has become an intensive research area. The importance pertaining to the planning newlineand control of a solar farm, wind farm, and energy system are based on the forecast of the newlinespot on the solar irradiance forecasting and wind power forecasting. In the past decades, newlinenumerous researchers suggested various approaches for the wind power and solar irradiance newlineforecasting models, but still, an exact wind power and solar irradiance prediction are of high newlinethrust newline