A survey on optimization strategies for energy storage and microgrid energy management in cyber-physical systems based microgrids

Abstract Rapid urbanization, population growth, and technological advancements over the past decade have significantly increased global energy demand. Renewable energy systems, which reduce environmental impacts and offer socio-economic benefits, are being increasingly integrated into conventional electricity grids. However, the integration of renewable energy introduces variability and unpredictability into energy management. To address these challenges, optimal energy management strategies are essential to ensure system reliability and efficiency. This article offers an extensive examination of diverse optimisation methods utilised in energy management within Cyber-Physical Systems (CPS)-based microgrids. It focuses on forecasting, demand management, economic dispatch, and unit commitment. The review highlights that conventional and heuristic approaches remain widely used due to their simplicity and effectiveness in solving microgrid energy management problems. Meanwhile, multi-agent-based methods and meta-heuristic algorithms show superior performance in CPS-based microgrids, as they effectively address the decentralized and dynamic nature of such systems. However, the manuscript also reveals that advanced optimization techniques remain underutilized in forecasting and demand management within CPS-based microgrids, underscoring the need for more accurate scheduling and predictive algorithms. Finally, the article emphasizes the importance of developing holistic energy management frameworks for CPS-based microgrids, incorporating features such as transactive energy models and collaborative energy sharing in community microgrids.