Fundamentals Of Energy Management System In Grid With Storage Using Converter Topology

Abstract

The objective of this paper is to provide basic insights associated with optimal operation of an AC microgrid system against system uncertainties. In specific, the energy management methods addressed to solve the problem of system uncertainties/requirements is focused at fundamental level with the consideration of all the possible options. Therefore, in order to satisfy technological and financial restrictions while coordinating generation, storage, loads, and grid interaction, an Energy Management System (EMS) is needed. The principles of optimum energy management algorithms for AC microgrids are thoroughly examined in this work. The energy management problem's mathematical formulations, goal functions, operational limitations, forecasting needs, and key optimization techniques are all examined in this work. Metaheuristic algorithms, model predictive control, stochastic and robust optimization, multi-agent systems, and artificial intelligence-based methods are contrasted with traditional approaches like linear programming, nonlinear programming, mixed-integer linear programming, and mixed-integer nonlinear programming. Economic dispatch, battery scheduling, peak-load reduction, grid interaction, renewable energy use, and emission minimization are all given special consideration. In terms of computing complexity, uncertainty handling, scalability, and real-time implementation, the benefits and drawbacks of various algorithms are assessed. Lastly, new avenues for study are explored, including distributed EMS architectures, cybersecurity, data-driven forecasting, hybrid optimization, reinforcement learning, and real-world validation. The constraints pointing to system requirement along with operational objectives are discussed. Further, the methods pertaining to optimal system operation are categorized based on the outcome of employed optimization method. The overview of reported methods in the literature for each category is briefly discussed.