Forecasting renewable energy efficiency significantly impacts system management and
operation because more precise forecasts mean reduced risk and improved stability and …

As widely used for secondary energy storage, lithium-ion batteries have become the core
component of the power supply system and accurate remaining useful life prediction is the …

While the field of electricity price forecasting has benefited from plenty of contributions in the
last two decades, it arguably lacks a rigorous approach to evaluating new predictive …

In order to reduce the negative impact of the uncertainty of load and renewable energies
outputs on microgrid operation, an optimal scheduling model is proposed for isolated …

In order to identify power production and demand in realtime for efficient and dependable
management for diverse renewable energy systems, precise and intuitive renewable energy …

Renewable energy is essential for planet sustainability. Renewable energy output
forecasting has a significant impact on making decisions related to operating and managing …

In recent years, digitalisation has rendered machine learning a key tool for improving
processes in several sectors, as in the case of electrical power systems. Machine learning …

A virtual power plant (VPP) refers to an active aggregator of heterogeneous distributed
energy resources (DERs), which creates a promising pathway to expand renewable energy …

This article presents a state-of-the-art review of the status, development, and prospects of
DC-based microgrids. In recent years, researchers' focus has shifted to DC-based …

We extend neural basis expansion analysis (NBEATS) to incorporate exogenous factors.
The resulting method, called NBEATSx, improves on a well-performing deep learning …