The main and pivot part of electric companies is the load forecasting. Decision-makers and
think tank of power sectors should forecast the future need of electricity with large accuracy …

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 …

In this paper, we performed an analysis of the 500 most relevant scientific articles published
since 2018, concerning machine learning methods in the field of climate and numerical …

This study introduces a power forecasting model, the convolutional neural network (CNN)–
long short-term memory (LSTM)–attention mechanism (AM) algorithm (CNN–LSTM–AM) …

This review paper provides a summary of methods in which artificial intelligence (AI)
techniques have been applied in the management of variable renewable energy (VRE) …

Effective short-term wind power forecast is essential for adequate power system stability,
dispatching and cost control. There are various significant renewable energy sources …

Load forecasting is a crucial task, which is carried out by utility companies for sake of power
grids' successful planning, optimized operation and control, enhanced performance, and …

Studies have demonstrated that changes in the climate affect wind power forecasting under
different weather conditions. Theoretically, accurate prediction of both wind power output …

The use of renewable energy sources (RESs) at the distribution level has become
increasingly appealing in terms of costs and technology, expecting a massive diffusion in the …

Accurate prediction of short-term wind power plays an important role in the safe operation
and economic dispatch of the power grid. In response to the current single algorithm that …