Reactive power optimization of power system with wind farm

被引：0
|
作者：
Wang, Hong [1 ,2 ]
Wang, Zhijie [1 ]
机构：
[1] Shanghai Dianji Univ, Shanghai 201306, Peoples R China
[2] Tongji Univ, Sch Econ & Management, Shanghai, Peoples R China
来源：
PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019) | 2019年
关键词：
Power system; reactive power optimization; intelligent algorithm; modeling and simulation;
D O I：
10.1109/ccdc.2019.8832415
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The RX model is used to solve the problems that occur when the wind farm is connected to the power system. In order to ensure the stable operation of the system, the access nodes are determined according to the reactive power regulation capability of the node and the active power loss of the system, and the improved fill function particle group is used. The algorithm optimizes the reactive power optimization model with wind farm. The simulation experiments show that the improved fill function particle swarm optimization algorithm is more advantageous than the filled function particle swarm optimization algorithm and the standard particle swarm optimization algorithm in both convergence accuracy and speed. It is also used in complex reactive power optimization problems of wind farms. Can be well applied, with practical application value.
引用
收藏
页码：5768 / 5771
页数：4
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