考虑多类型储能系统时空灵活性支撑的配电网日前优化调度策略

A day-ahead optimal scheduling strategy for distribution networks with spatiotemporal flexibility support of multi-type energy storage systems

大规模分布式资源的接入使配电网的调控更加困难,如何合理有效地利用多元化资源以降低配电网的运行成本成为亟待解决的关键技术问题。考虑可移动式储能系统和电动汽车的互补特性,提出一种考虑多类型储能系统时空灵活性支撑的配电网日前优化调度策略,提高配电网系统的运行经济性。首先,建立电动汽车和可移动式储能系统的调度模型,并建立电动汽车停车生成率模型,简化了模型的复杂度,提高了求解效率;其次,引入基于集合的改进粒子群算法,并将其改造为适用于配电网优化调度的求解算法,提高其在离散空间寻优的求解效率;最后,在IEEE 33节点配电系统中对所提出的协同优化调度策略进行仿真分析,验证所提策略的有效性。

The access of large-scale distributed resources makes the regulation and control of the distribution grid more difficult,and how to reasonably and effectively utilize diversified resources to reduce the operating cost of the distribution grid has become a key technical problem to be solved.Considering the complementary characteristics of removable energy storage systems and electric vehicles,a day-ahead optimal scheduling strategy for distribution grids with the support of temporal and spatial flexibility of multiple types of energy storage systems is proposed to improve the operating economy of the distribution grid system.Firstly,the scheduling models of electric vehicles and removable energy storage systems are established and the electric vehicle parking generation rate model is built,which simplifies the complexity of the model and improves the solution efficiency.Secondly,the ensemble-based improved particle swarm algorithm is introduced and adapted to be suitable for the optimal scheduling of distribution grids,which improves the solution efficiency of its optimization search in discrete space.Lastly,simulation analysis conducted on the IEEE 33-bus distribution system verifies the effectiveness of the proposed coordinated optimization scheduling strategy.