Microgrid technologies for energy storage and control: A review of advanced optimization approaches for renewable and hybrid energy systems

This paper reviews methodologies and technologies for optimizing hybrid renewable energy systems (HRESs) and microgrid operations, addressing key challenges such as sustainability, compatibility, environmental impact, and cost-effectiveness. It covers a wide range of topics, including renewable energy integration, energy storage, heat pump systems, control methods, and optimization techniques. The review highlights the role of storage systems in managing renewable energy intermittency, explores various storage alternatives, and heat pump-based electrical-to-thermal energy conversion, and examines innovative control strategies. It also assesses different modeling methodologies and optimization algorithms for components like photovoltaic systems, wind turbines, biomass energy, and energy storage. This paper presents a dynamic energy management operation strategy for optimizing HRESs. Also, a comparative analysis of various optimization techniques based on their targeted parameters, such as energy storage system optimization, network/operational policy optimization. The study systematically maps electrochemical, electro-thermal, equivalent circuit, data-driven, and hybrid physics–Artificial Intelligence battery models with their suitable optimization algorithms, and also includes the specialty of each optimization technique and its convergence speed. A performance comparison is presented detailing key indicators such as efficiency, capacity factor, and cost for each technology. We also examine capacity and demand matching to show how well different technologies align with energy demand profiles over time. Finally, a mixed integer linear programming-particle swarm optimization-based hybrid optimization algorithm for efficient power scheduling in a microgrid is proposed, and a proposed flow chart of the energy management system's operation strategy is developed to guide optimal control of power flow and resource usage. This integrated approach provides valuable insights for optimizing microgrid designs and operational strategies.