考虑主动管理措施的配电网无功补偿双层优化配置

为了适应未来大量分布式电源(DG)并网及自动化水平显著提高的主动配电网发展，在规划阶段应该考虑主动管理措施，优化系统运行方式。同时，现有的无功补偿规划研究忽略了DG及负荷的不确定性。为此，计及间歇性DG及负荷的不确定性，提出主动配电网无功补偿双层优化配置模型。上层规划以无功补偿电容器的投资成本、网络损耗费用综合最优为目标函数，下层规划在此基础上考虑调节无功补偿容量及调节有载变压器抽头两种主动管理措施，对每个场景进行优化。采用K-均值聚类法对场景进行缩减，结合和声搜索算法和粒子群算法联合求解模型。通过IEEE33节点算例进行仿真计算，验证所提模型和方法的正确性。

Bi-level optimal allocation of reactive power compensation considering active management measure

In order to adapt to active distribution network which will have large-scale distributed generation (DG) and high level of automation in the future, active management measures must be considered in the planning stage to optimize system operation. And the existing research of distribution network reactive compensation planning ignores the uncertainty of DG and load. Aiming to solve the problems, this paper proposes reactive compensation optimal allocation model in active distribution network based on the uncertainties of intermittent DG and load power. The lowest reactive compensation capacitors investment cost and network loss cost are taken as the objective of upper level. And considering two active management measures including regulating reactive power compensation capacity and regulating the on-load tap changer, the lower level optimizes for each scene. This paper uses K- means clustering method to reduce the scene, and combines with the harmonic search algorithm and particle swarm algorithm to solve the model. And simulative results of IEEE-33 distribution system verify the effectiveness of the model and solution methods. This work is supported by National High-tech R & D Program of China (863 Program) (No. 2014AA051901).