Genetic Algorithm Based Modeling of Doubly-Fed Wind Farms

Yujia Gu, Yinfeng Wang, Xutao Li, Bei Tian, Feng Gao and Chao Lu Power Science Research Institute of State Grid Ningxia Power Co., Yinchuan, China 750011 Tsinghua University, Beijing, China 100084 Corresponding author Abstract—Faced with the drawback of conventional doubly-fed wind farm models, which cannot reliably reflect the actual control law and dynamic characteristics, a method of complex characteristics modeling based on simulation is developed in this paper. The software MATLAB/Simulink platform is utilized to create a universal equivalent model, including structure characters and control modes. In order to make the parameters identification process of higher-order wind farm models simplifier,trajectory sensitivity analysis method is used to select dominant dynamic parameters. Besides, a method melting the bright side of model simulation and the genetic algorithm is proposed to search the optimal parameter combination. The test results on the IEEE 9-bus system demonstrate the effectiveness of the proposed comprehensive method.