The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …

Energy systems undergo major transitions to facilitate the large-scale penetration of
renewable energy technologies and improve efficiencies, leading to the integration of many …

This article proposes a hybrid policy-based reinforcement learning (HPRL) adaptive energy
management to realize the optimal operation for the island group energy system with energy …

Due to increasing complexity, uncertainty and data dimensions in power systems,
conventional methods often meet bottlenecks when attempting to solve decision and control …

With large-scale integration of renewable generation and distributed energy resources,
modern power systems are confronted with new operational challenges, such as growing …

In this paper, an intelligent multi-microgrid (MMG) energy management method is proposed
based on deep neural network (DNN) and model-free reinforcement learning (RL) …

Microgrids are gaining popularity by facilitating distributed energy resources (DERs) and
forming essential consumer/prosumer centric integrated energy systems. Integration …

This paper evaluates the design and optimization of an islanded hybrid microgrid for various
load dispatch strategies by assessing the optimal sizing of each component, the power …

The dynamic nature of sustainable energy and electric systems can vary significantly along
with the environment and load change, and they represent the features of multivariate, high …

Energy consumption is increasing rapidly; hence, the energy demand cannot be fulfilled
using traditional power resources only. Power systems based on renewable energy …