This article presents a review of current advances and prospects in the field of forecasting
renewable energy generation using machine learning (ML) and deep learning (DL) …

Energy crisis and climate change are the major concerns which has led to a significant
growth in the renewable energy resources which includes mainly the solar and wind power …

Variability in solar irradiance has an impact on the stability of solar systems and the grid's
safety. With the decreasing cost of solar panels and recent advancements in energy …

The intermittency of solar energy resources has brought a big challenge for the optimization
and planning of a future smart grid. To reduce the intermittency, an accurate prediction of …

Smart agricultural sensing has enabled great advantages in practical applications recently,
making it one of the most important and valuable systems. For outdoor plantation farms, the …

The advanced development of large-scale solar power plants (LSSPs) has made it
necessary to improve accurate forecasting models for the output of solar energy. Solar …

Air pollution (mainly PM2. 5) is one of the main environmental problems about air quality. Air
pollution prediction and early warning is a prerequisite for air pollution prevention and …

Forecasting wind speed is one of the most important and challenging problems in the wind
power prediction for electricity generation. Long short-term memory was used as a solution …

Solar energy becomes widely used in the global power grid. Therefore, enhancing the
accuracy of solar energy predictions is essential for the efficient planning, managing and …

Accurate solar generation prediction is of great significance for grid dispatching and
operation of photovoltaic power plants. In this paper, we propose a novel solar generation …