摘要
随着风电装机容量的增加,风电机组并网对电力系统安全稳定运行的影响日益显著。为了实现低电压穿越(LVRT)期间双馈风电系统的稳定性分析与计算,需要建立能准确描述实际输出外特性的双馈风电系统模型。然而由于变流器控制系统是黑箱结构,其控制模型和控制参数通常难以获取,因此仿真模型与实际系统的外特性响应往往存在显著偏差。为了进一步提高模型的准确度,本文提出了一种考虑双馈风电机组低压穿越序贯控制的全局参数辨识方法。首先计及低电压期间的序贯控制特性,建立双馈风电系统的精细化数学模型,其次基于轨迹灵敏度法选取最佳观测量,提出了多工况-分步辨识策略,利用多组实测数据对双馈风电系统的全局控制参数进行辨识。最后在不同电压跌落程度情况下进行波形对比和模型验证,验证结果表明所提辨识方案可准确模拟实际双馈风电系统的输出外特性。
With the increasing installed wind power capacity,the grid-connected wind turbines have a significant impact on the power system.In order to realize the stability analysis and calculation of the doubly fed induction generator(DFIG)wind power generation system during the low voltage ride-through(LVRT)period,it is necessary to establish a model of the DFIG wind power generation system which can accurately describe the external characteristics of the actual system.However,because the converter control system is a black box structure,its control model and control parameters are often difficult to obtain,so there is a significant deviation between the simulation model and the actual system.Therefore,in order to improve the accuracy of the model,this paper proposed a global parameter identification method which can consider LVRT sequential control of DFIG.Firstly,an accurate mathematical model of the system is established which takes into account the sequential control characteristics during LVRT period.Then,the best observations are selected based on the trajectory sensitivity method,and the multi-condition-step identification strategy is proposed.In addition,the global control parameters are identified with several groups of experimental data.Finally,waveform comparison and model verification are carried out under different voltage sag conditions.The verification results show that the proposed identification scheme can accurately simulate the external characteristics of actual DFIG wind generation system.
作者
方欣
姚骏
刘育明
陈朝阳
李小菊
李登峰
LVRT FANG Xin;YAO Jun;LIU Yuming;CHEN Zhaoyang;LI Xiaoju;LI Dengfeng(State Key Laboratory of Power Transmission Equipment Technology(Chongqing University),Chongqing 400044,China;State Grid Chongqing Electric Power Research Institute,Chongqing 401123,China)
出处
《电工电能新技术》
CSCD
北大核心
2024年第2期1-11,共11页
Advanced Technology of Electrical Engineering and Energy
基金
国家自然科学基金项目(51977019)
国网重庆市电力公司科技项目(522023220010)。