With the increasing prominence of the energy crisis and environmental problems, microgrid technology has received widespread attention as an important technical means to improve the stability and reliability of new energy access. Focusing on the latest development of microgrid operation control technology, this paper combs and summarizes the related research at home and abroad, including the key technologies of microgrid optimization operation, power prediction and virtual synchronous active support control technology, and points out their advantages and limitations. First, this review describes the concept and structure of microgrids, including components such as distributed power sources, energy storage devices, energy conversion devices and loads. Then, the microgrid optimization operation technologies are analyzed in detail, including energy management optimization algorithms for efficient use of energy and cost reduction. Focusing on microgrid power forecasting techniques, including wind energy and PV power forecasting and load forecasting, the contributions and impacts of different power forecasting methods are summarized. Furthermore, the inverter control strategies and the stability mechanism of the virtual synchronous generator (VSG) active support control technology are investigated. Finally, synthesizing domestic and international microgrid development experience, this review summarizes the current state-of-the-art technologies, analyzes the advantages and limitations of these key technologies (including optimization scheduling, power prediction and VSG-based active support control) and highlights the necessity of their continuous improvement to provide a solid foundation for promoting the widespread application and sustainable development of microgrid technology.

With the increasing proportion of renewable energy in power systems, the applications of mobile energy storage systems (MESSs) with better flexibility and controllability are becoming more widespread. To further explore the hybrid ESS optimization scheduling problem of MESS and SESS, this paper first quantifies parts of actual road topologies in Dali City, China, and combines the Dijkstra algorithm to obtain an MESS path optimization framework. Subsequently, a hybrid ESS optimization scheduling model combining MESS and SESS is constructed with the objective functions of maximizing the scheduling benefits of the hybrid ESS and minimizing system voltage deviation. Finally, the non-dominated sorting genetic algorithm III (NSGA-III) is used to solve the hybrid ESS optimization scheduling model. To verify the effectiveness of the proposed method, this paper selected typical daily load and renewable energy output data in winter in Dali for the case study. The final result shows that the total profit of the optimized scheduling of the hybrid ESS is CNY 578, of which the arbitrage income is CNY 1119.2 and the total cost is CNY 540.44. Meanwhile, the voltage distribution range and total power loss are optimized from [0.9616, 1.0105] to [0.9723, 1.0008] and 0.963 MW to 0.9134 MW, which indicates that the coordinated scheduling of hybrid ESS is the key to improving the reliability of distribution network operation, and the path optimization of MESS is crucial for enhancing its profitability.