The optimal co-planning of the integrated energy system (IES) and machine learning (ML)
application on the multivariable prediction of IES parameters have mostly been carried out …

The demand for energy generation from solar energy resource has been exponentially
increasing in recent years. It is integral for a grid operator to maintain the balance between …

To counter the challenges posed by the unpredictability of wind velocities on wind energy
production, a wind speed prediction model combining chaotic map**-based particle …

Accurate prediction of wind speed plays a very important role in the stable operation of wind
power plants. In this study, the goal is to establish a hybrid wind speed prediction model …

Accurate ultra-short-term wind power forecasting is a prerequisite for decision making
related to the management of power systems. Existing approaches used to forecast wind …

Promoting renewable energy sources, particularly in the solar industry, has the potential to
address the energy shortfall in Central Africa. Nevertheless, a difficulty occurs due to the …

Recent advancements in data science and artificial intelligence, as well as the development
of clean and sustainable energy sources, have created numerous opportunities for energy …

The accuracy and stability of wind power forecasting are very important for the operation of
wind farms. However, for the newly built wind farms without sufficient historical data, it is …

Wind speed forecasting (WSF) accuracy is vital for exploiting renewable and environment-
friendly wind energy. Therefore, a hybrid WSF model, namely VIL (VMD-ICEEMDAN-LSTM) …

The increasing interest in renewable microgrids have motivated the exploration of more
sustainable alternatives to traditional energy supply. In this study, a novel hybrid renewable …