The use of intelligent algorithms for global solar prediction is an ideal tool for research
focused on the use of solar energy. Forecasting solar radiation supports different …

Renewable energy sources have gained greater importance in the past decade owing to the
continuous growth in energy demand of developing nations. The modular nature of solar …

To enhance the forecasting of solar radiation strength on horizontals, an ensemble learning
approach is proposed. Two types of machine learning models are arranged to predict solar …

The integration of Solar Energy in smart grids and many utilities is continuously increasing
due to its environmental and economical benefits. However, the uncertainty of available …

Being at the cutting edge for a long time, solar energy has found several applications in
various areas. Optimal harvesting of solar energy is one of the thrust areas of the …

In recent years, strong photovoltaic systems are now more necessary than ever, and this
development has been accompanied by the demand for diagnostic systems characterized …

It is well known that the variability in PV power output is primarily owing to fluctuations in
radiation received by the solar panels. Forecasting in the short-term horizon particularly is …

To solve the problems of nonlinearity and power fluctuation linked on the Photovoltaic panel
(PV) connected storage system and grid, because of the temperature and irradiation …

In this work an improved KELM based forecasting model is being proposed, which attains a
specific level of prediction of solar irradiance affecting PV power management. The new …

Solar power grid integration has increased tremendously in the global electricity market.
However, further increase in solar power grid integration has been restricted by the …