A comprehensive review of microgrid control methods: Focus on AI
Effective control systems are essential for ensuring smooth integration, managing energy storage systems, and maintaining microgrid safety. In this study, a review of recent control methods
Power Electronics-Based Operation for Intelligent Energy
We provide five propositions of combined hybrid control algorithms for intelligent energy management that minimize the cons of single control methods and improve the control operation in
Smart Energy Management for Residential PV Microgrids: ESP32
This article introduces a cost-effective, IoT-enabled flexible energy management system (EMS) for residential photovoltaic (PV) microgrids with battery storage, implemented on an ESP32
IoT-integrated smart energy management system with enhanced ANN
Abstract This research paper focuses on an intelligent energy management system (EMS) designed and deployed for small-scale microgrid systems. Due to the scarcity of fossil fuels and the occurrence of
A review of intelligent control strategies for energy management
The rapid integration of renewable energy sources into modern power systems has transformed the traditional grid paradigm, giving rise to localized microgrids, intelligent, and semi
Advancements and Challenges in Microgrid Technology: A
The concept of microgrids (MGs) as compact power systems, incorporating distributed energy resources, generating units, storage systems, and loads, is widely acknowledged in the
Optimized Intelligent Controller for Energy Storage based
This study focuses on a sustainable microgrid-based hybrid energy system (HES), primarily focusing on analyzing the performance of the fuel cell and its impact
A Reinforcement Learning Approach for Optimal Control in
Abstract—The increasing integration of renewable energy sources (RESs) is transforming traditional power grid networks, which require new approaches for managing decentralized en-ergy production
A review of control strategies for optimized microgrid operations
Efficient and intelligent control strategies are crucial for optimizing MG operations and maximizing the utilization of distributed energy resources, storage systems, networks, and loads.
Intelligent RBF neural network-based control for dynamic
The control and process of microgrids in the occurrence of Hybrid Renewable Energy Sources (HRES) are developed in this research.