Virtual power plants possess the capability to effectively manage the inherent conflict
between dispersed electricity generation and user demand, hence optimising market …

This study uses an artificial neural network (ANN) as an intelligent controller for the
management and scheduling of a number of microgrids (MGs) in virtual power plants (VPP) …

The objective of this work has been to implement an orderly, accessible, fast and space-
saving storage system that allows the transfer to a Relational Database Management …

This paper introduces a novel approach to speed-sensorless predictive torque control (PTC)
in an autonomous wind energy conversion system, specifically utilizing an asymmetric …

Due to the increase in electric energy consumption and the significant growth in the number
of electric vehicles (EV) at the level of the distribution network, new networks have started …

Due to rapid socioeconomic growth and current environmental concerns, reducing global
greenhouse gas emissions is a key step toward sustainable development. In recent years …

To tackle the variability of distributed renewable energy (DRE) and the timing differences in
load demand, this paper perfects the integrated layout of “source− load− storage” energy …

In light of the growing urgency surrounding energy and environmental concerns, this paper
presents a two-layer iterative energy dispatch strategy tailored for a multi-energy-flow virtual …

This study uses an artificial neural network (ANN) as an intelligent controller for the
management and scheduling of a number of microgrids (MGs) in virtual power plants (VPP) …

This paper presents a new optimal controller using the Binary Gradient Descent (BGD)
algorithm to manage distributed generations effectively in a grid network. The algorithm aims …