Next-Generation Microgrids: Control, Intelligence and Resilience

Abstract

Microgrids (MGs) are viewed as small and versatile power generation systems which incorporate distributed energy resources, generation systems, energy storage systems, and local loads. There are countries around the globe that are embracing MG technologies to help secure access to cleaner, lower cost, and more sustainable energy supplies. The effective operation of MGs continues to be hindered by a number of technical and non-technical issues, such as system stability, power quality, energy management inherent limitations, cyber security threats, regulatory restrictions, economic considerations, market-related challenges, and poor market penetration. This paper is a systematic literature review of latest improvements in MG technology. It discusses on MG architectures and control goals, methodological approaches, emerging control techniques, challenges in future, and possible solutions. Special focus is placed on current frequency and voltage stability controls, energy management controls and threat mitigation controls. The review, which is also quite comprehensive, covers a wide variety of engineering and non-engineering issues that have arisen in MG systems and outlines possible strategies for mitigating these issues. Further, the paper analyzes some recent control strategies for frequency regulation in an MG system and provides simulation using MATLAB software to showcase its functioning. The research also examines the applications of sophisticated technologies like machine learning, blockchain, reinforcement learning, neural networks, edge computing, and the Internet of Things (IoT) for solving challenges related to the scalability of MG systems. Finally, the paper summarizes the major findings, outlines directions for future research, and offers a comprehensive overview of the state of-the-art and the outlook of the field of MG research.