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文章摘要
基于神经网络逆系统方法的链式STATCOM线性化解耦控制
Linearization and decoupling control of cascade STATCOM based on neural network inverse system method
Received:March 25, 2015  Revised:July 08, 2015
DOI:
中文关键词: 链式STATCOM  神经网络逆系统  线性化解耦控制  双变量
英文关键词: cascade STATCOM, neural network inverse system, linearization and decoupling control, double variable
基金项目:
Author NameAffiliationE-mail
Liu Qingfeng* College of Electrical and Information Engineering,Changsha University of Science and Technology 317569218@qq.com 
Su Shiping College of Electrical and Information Engineering,Changsha University of Science and Technology  
Liu Guiying College of Electrical and Information Engineering,Changsha University of Science and Technology  
Lv Chao College of Electrical and Information Engineering,Changsha University of Science and Technology  
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中文摘要:
      针对链式STATCOM补偿负载无功电流以及稳定电网电压的控制问题,本文建立了链式STATCOM在稳态情况下的数学模型,分析了在补偿容性负载时移相角δ与无功电流的关系,推导了装置的动态模型,得出了双变量(移相角与调制比)和电流的关系式,提出了一种基于神经网络逆系统控制方法,通过对该链式STATCOM系统可逆的验证、神经网络的构建以及控制系统的设计,实现了链式STATCOM输出的有功-无功电流的线性化解耦控制。仿真结果表明,该控制策略具有良好的动态效果,使得装置具有较好的抗参数变化、抗负载扰动性能。从而验证了该控制策略的有效性及可行性。
英文摘要:
      Aiming at the control problem of cascade STATCOM to compensate the load reactive current and stabilize the grid voltage, this paper establishes a mathematical model of cascade STATCOM under the steady state, analysis the relationship of phase angle δ and reactive current on compensating capacitive load, deducts the establishment of dynamic model of the device, obtains the relationship between the two variables δ、M and current, this paper proposes a control method based on neural network inverse system, through the verification of reversibility of the system, construction of neural network and the design of control system, realizing the linearization and decoupling control of active and reactive current of cascade STATCOM. The simulation results show that the control strategy has favourable dynamic performance, so that the device has better performance of anti parameters change and load disturbance. It illustrates the effectiveness and the feasibility of the control strategy.
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