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文章摘要
基于广域测量信号的双馈风电机组阻尼控制策略
WAMS-based Damping Control Strategy of Doubly-Fed Wind Generation System
Received:August 06, 2014  Revised:August 06, 2014
DOI:
中文关键词: 电力系统  低频振荡  双馈风电机组  阻尼控制  有功功率控制  无功功率控制
英文关键词: power system  low frequency oscillation  DFIG  dampingcontrol  active power control  reactivepower control
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
Author NameAffiliationE-mail
ZHU Xiao-rong* State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electric Power University ncepuzxr@163.com 
ZHANG Jian-chao State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electric Power University zhjc0316@163.com 
WANG Yi State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electric Power University  
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中文摘要:
      为了抑制电力系统的区域间低频振荡,本文提出了一种应用于双馈风电机组(DFIG)的附加阻尼控制策略。首先,建立了双馈风电机组的动态模型及其控制策略。然后阐明了动态有功功率注入和动态无功功率注入提高系统阻尼的原理,在此原理的基础上提出了双馈风电机组附加阻尼控制器的设计方法。阻尼控制器基于电力系统稳定器(PSS),将广域测量信号区域间同步机组电压相角差作为输入信号。考虑到DFIG有功功率和无功功率可解耦控制,控制器输出信号附加到DFIG有功功率控制环和无功功率控制环。最后,建立了四机两区域电力系统仿真模型,通过特征值分析和时域仿真分析验证了附加阻尼控制策略的有效性及动态功率注入提高系统阻尼原理的正确性。
英文摘要:
      This paper presents a supplementary control of doubly-fed induction generator (DFIG) to damp the inter-area oscillation. Firstly, the small signal dynamic model of DFIG was established. Secondly, the theory of dynamic active power injection and dynamic reactive power injection improving the system damping was proposed. A supplementary damping controller of DFIG was investigated by this theory. The controller was designed based on the power system stabilizer (PSS). The voltage phase angles difference obtained from the Wide Area Measurement Signals (WAMS) was selected as the input signal. Considering the capability of decoupled active power and reactive power control of DFIG, the supplementary damping controller was added to the active power control loop and reactive power control loop separately, and the effects of the control were analyzed. Finally, the proposed controller’s performance was accessed through eigenvalue analysis and time domain simulation.
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