摘要
针对传统的无功优化算法在求解含风电场的配电网无功优化问题时存在的局限性,充分考虑风电出力的随机性及间歇性,将风电机组作为连续的无功源参与电网的无功优化,针对1d中不同时段的风速变化情况,建立包含有功网损及电压偏差的综合无功优化模型,并提出一种基于子空间的细菌群趋药性算法(SIBCC)参与无功优化计算。最后以改进IEEE33节点系统为例进行仿真计算,验证了所提方法的有效性及实用性。
In view of the limitations of the traditional reactive power optimization algorithm in solving the problem of containing wind farm reactive power optimization of distribution network,considering the randomness and intermittence of wind power output,the wind turbine is regarded as continuous reactive power source to participate in reactive power optimization of power grid.Based on the change of wind speed at different time interval in one day,comprehensive reactive power optimization model with active network loss and voltage deviation was established,and an improved group bacterial chemotaxis algorithm based subspace（SIBCC）was proposed to optimize the reactive power.Finally,the IEEE33 node system was used as an example for simulation calculation,it verified the effectiveness and practicability of the proposed method.
出处
《水电能源科学》
北大核心
2016年第4期198-202,共5页
Water Resources and Power
关键词
风电场
双馈感应风电机组
无功优化
细菌群体趋药性算法
子空间
wind farm
doubly-fed induction wind turbine generator
reactive power optimization
bacterial colony chemotaxis algorithm
subspace
