A state of the art review on energy management techniques and optimal sizing of DERs in grid-connected multi-microgrids

In recent times, there has been a growing focus on multi-micro-grids (MMGs) system, owing to its well-suited structures for efficiently accommodating large-scale integration of distributed energy resources (DER). This attention is driven by the system’s cost-effectiveness, enhanced efficiency, stability, and reliability performance, achieved through the collaborative exchange of power flow among individual micro-grids (MGs) and the main grid. Fundamental strategies for attaining optimal energy flow and sharing involve the optimal sizing of MGs and the implementation of an Energy Management System (EMS). These strategies play a crucial role in addressing uncertainties associated with intermittent generation, load fluctuations and energy market dynamics. This paper offers a review of grid-connected MMG topologies, EMS structures, coordination methods and current optimization approaches designed to meet EMS objectives. To address the inherent volatilities, the paper introduces various uncertainty quantification techniques along with current challenges. Additionally, it suggests future directions, emphasizing intelligent and predictive modeling to handle uncertainties, as well as recommending the incorporation of energy storage systems (ESSs) to align with emerging trends.

近年来，多微电网（multi-micro-grids, MMGs）系统愈发受到关注，因其结构适配性优异，可高效支撑分布式能源（distributed energy resources, DER）的大规模并网接入。该系统获得广泛关注的动因在于，其可通过各微电网（micro-grids, MGs）与主电网间的功率流协同交互，实现成本效益提升、运行效率优化、稳定性与可靠性增强。实现最优能量流分配与共享的核心策略，包括微电网的优化配置以及能源管理系统（Energy Management System, EMS）的部署。此类策略对于应对间歇性发电、负荷波动与能源市场动态带来的不确定性具有关键作用。本文对并网型多微电网拓扑结构、能源管理系统架构、协同控制方法以及适配能源管理系统目标的主流优化手段进行了综述。针对固有的波动性问题，本文介绍了各类不确定性量化技术，并剖析了当前面临的挑战。此外，本文还展望了未来研究方向，强调需采用智能化与预测建模手段处理不确定性，并建议引入储能系统（energy storage systems, ESSs）以契合行业新兴发展趋势。