The accurate power generation forecast of multiple renewable energy sources is significant
for the power scheduling of renewable energy systems. However, previous studies focused …

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) …

With the rapid advancement of technology in the energy sector and the demand for
sustainable energy practices, the world is aiming at fostering the hydrogen economy and …

With the rapid advancement of the high-performance computing technology and the
increasing availability of the mass-storage memory device, the application of the data-driven …

This paper conducts a comprehensive study on the application of big data and machine
learning in the electrical power grid introduced through the emergence of the next …

Solar photovoltaic plants are widely integrated into most countries worldwide. Due to the
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …

Conventional fossil fuels are depleting daily due to the growing human population. Previous
research has proved that renewable energy sources, especially solar and wind, can be …

Variability of solar resource poses difficulties in grid management as solar penetration rates
rise continuously. Thus, the task of solar power forecasting becomes crucial to ensure grid …

Forecasting is a crucial task for successfully integrating photovoltaic (PV) output power into
the grid. The design of accurate photovoltaic output forecasters remains a challenging issue …

Accurate PV power forecasting techniques are a prerequisite for the optimal management of
the grid and its stability. This paper presents a review of the recent developments in the field …