Dong Liu

Smart grids are the ultimate goal of power system development. With access to a high proportion of renewable energy, energy storage systems, with their energy transfer capacity, have become a key part of the smart grid construction process. This paper first summarizes the challenges brought by the high proportion of new energy generation to smart grids and reviews the classification of existing energy storage technologies in the smart grid environment and the practical application functions of energy storage in smart grids. Secondly, optimization planning and the benefit evaluation methods of energy storage technologies in the three different main application scenarios, including the grid side, user side, and new energy side, are analyzed. The advantages and shortcomings of the current research are also pointed out. Furthermore, the paper sheds light on the pressing issues that demand further consideration in energy storage planning. Finally, the aspects that warrant attention in the future application and promotion processes are elucidated in detail, culminating in a comprehensive understanding of the energy storage technologies in smart grids.

Isolated power systems (IPS) usually have multifaceted operational objectives in engineering scenarios, and many key tasks are performed by multiple pulsed loads. The research on multi-objective energy optimal scheduling in isolated power systems which contain multiple pulsed loads is the subject of this paper. In addition, optimal mobility and maximum multiple pulsed load performance value are discussed. By introducing the concept of ship speed at the end state, isolated power system maneuverability is properly characterized by the final state ship speed, combined with the maximum efficiency of multiple pulsed loads, and a multi-objective optimization model of weighted form is constructed using a general, given solution method. In addition, two specific solutions regarding typical engineering scenarios are proposed in this paper: accelerating the catch-up situation and accelerating the evacuation situation. Algorithms for general situations and specific solutions regarding typical engineering scenarios are proposed. Study cases regarding specific engineering scenarios are demonstrated to verify the correctness and efficiency of the method. Finally, the limitations and shortcomings of the established methodology are emphasized.