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山地风电场采用柔性直流输电的WNN控制

闫婧,王灵梅   

  1. (山西大学自动化系,太原030013)
  • 收稿日期:2017-03-12 修回日期:2017-04-13 出版日期:2017-12-27 发布日期:2017-12-15
  • 作者简介:闫婧(1990—),女,山西吕梁人,硕士研究生,研究方向为柔性直流输电控制.
  • 基金资助:
    山西省煤基重点科技攻关项目(MD2014-06)

Research on flexible direct current transmission based on WNN control for mountain wind farm

YAN Jing, WANG Lingmei   

  1. (Department of Automation, Shanxi University, Taiyuan 030013, China)
  • Received:2017-03-12 Revised:2017-04-13 Online:2017-12-27 Published:2017-12-15

摘要: 针对随机性和波动性特点显著的某山地风电场,在采用MMC 柔性直流输电技术时,常规的PI 控制面对复杂的工况存在稳态误差大和响应速度慢的问题。小波神经网络(WNN)具有逼近任意非线性函数的特点,因此提出了将WNN 用于柔性直流输电中外环电压控制的方法,在软件PSCAD/EMTDC 和Matlab/Simulink中,分别搭建系统的电气部分和WNN 控制部分,完成对整个系统的仿真验证。仿真结果表明,WNN 控制策略具有很好的动态特性,对大规模可再生能源并网具有指导性作用。

关键词: 山地风电场, 柔性直流输电系统, PI控制, 小波神经网络

Abstract: Aiming at the significant characteristics of randomness and volatility of a wind farm, there exist problems of steady-state error and slow response speed under conventional PI control based on MMC flexible HVDC technology. WNN (wavelet neural network)is applied to the outer ring of voltage control due to its characteristic of approximating any nonlinear function. PSCAD/EMTDC and Matlab/Simulink are used to build system of electrical part and WNN control part respectively. Simulation results show that WNN control strategy has good dynamic characteristics and better guiding effect for large-scale renewable energy grid.

Key words: mountain wind farm, flexible HVDC transmission system, PI control, WNN

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