基于改进自适应陷波的双馈风电场时变次同步振荡抑制策略

Time-varying Subsynchronous Oscillation Mitigation Strategy for DFIG Wind Farms Based on Improved Adaptive Notch Filter

双馈风电场经串补电容并网时,可能引发次同步控制相互作用(subsynchronous control interaction,SSCI),严重威胁系统安全稳定运行。通过在风机控制器中引入陷波器可有效阻断SSCI,然而固定参数陷波器难以适应实际系统中次同步振荡表现出的频率大范围时变特征。为解决这一问题,该文提出一种基于改进自适应陷波(adaptive notch filter,ANF)的双馈风电场时变次同步振荡抑制策略。首先,分析ANF安装于风机转子侧变流器(rotor-side converter,RSC)不同位置时对次同步振荡分量的阻断效果,确定ANF的最佳安装位置;其次,基于紧缩技术近似投影子空间跟踪算法(projection approximation subspace tracking based on the deflation technique,PASTd)在线获取次同步振荡信息,提出总体控制架构,设计基于量测数据辨识的ANF中心频率更新策略;最终,在考虑风速、风机台数、无功出力、电网拓扑变化等多种影响因素的情况下,验证控制策略对频率时变次同步振荡的抑制效果。与现有方法相比,所提控制策略不依赖于系统的准确数学模型,且具备较强的鲁棒性和适应性。

Subsynchronous control interaction(SSCI) may be triggered when DFIG-based wind farms are connected to the grid via series-compensated capacitors,which seriously threatens the safe and stable operation of the system.Embedding notch filters into the DFIG converter controllers can mitigate SSCI effectively.However,the fixed-parameter notch filter is difficult to adapt to the time-varying frequency characteristic of the subsynchronous oscillation in the actual system.To address the issue,a time-varying subsynchronous oscillation mitigation strategy based on the improved adaptive notch filter for DFIG-based wind farms is proposed in this paper.First,effects on blocking the subsynchronous oscillation component are analyzed when the ANF is installed at different positions of the rotor-side converter(RSC),and the best installation location of the ANF is determined.Second,the overall control framework is designed,and the strategy for ANF center frequency updating based on measurement data is developed.Finally,considering multiple influential factors such as wind speed,number of wind turbines,reactive power output,grid topology,etc.,the performance of the proposed control strategy in mitigating subsynchronous oscillations with time-varying frequency is verified.Compared with the existing methods,the proposed method is independent of the accurate mathematical model of the system and presents stronger robustness and adaptability.