Forecasting of solar radiation (Radn) can provide an insight vision for the amount of green
and friendly energy sources. Owing to the non-linearity and non-stationarity challenges …

The increase in the use of renewable energy sources (RES) has been remarkable in recent
years, especially photovoltaic energy, which is one of the most widely used renewable …

The volatile behavior of solar energy is the biggest challenge in its successful integration
with existing grid systems. Accurate global horizontal irradiance (GHI) forecasting can …

Accurate solar irradiance prediction is crucial for harnessing solar energy resources.
However, the pattern of irradiance sequence is intricate due to its nonlinear and non …

The installed capacity of photovoltaic power generation occupies an increasing proportion in
the power system, and its stability is greatly affected by the fluctuation of solar radiation …

Precise solar radiation forecasting can provide great benefits and solutions for smart grid
distribution and electricity management. However, its non-stationary behavior and …

Accurate prediction of solar irradiance is beneficial in reducing energy waste associated
with photovoltaic power plants, preventing system damage caused by the severe fluctuation …

Forecasting solar irradiance is of utmost importance in supplying renewable energy
efficiently and timely. This paper aims to experiment five variants of recurrent neural …

Short-term solar irradiance forecasting (STSIF) is of great significance for the optimal
operation and power predication of grid-connected photovoltaic (PV) plants. However …

Accurate and reliable solar radiation forecasting is of great significance for the management
and utilization of solar energy. This study proposes a deep learning model based on Bi …