基于滤波提取及滑窗算法的短路比在线辨识方案

Online Identification Scheme for Short Circuit Ratio Based on Filter Extraction and Sliding Window Algorithm

随着“双高”趋势给电网带来的弱网稳定性威胁,为实现对电网强度的实时监测,需进行短路比的在线辨识。许多辨识方法均需设计复杂的谐波提取算法或采用高精度高速率的采样分析仪器,操作困难,成本较高。为降低短路比辨识难度,设计了基于滤波特性的扰动响应分量提取方法及数据检离群滑窗算法,并搭建了2.5 MW风电机组并网模型。仿真结果表明:短路比辨识误差在5%以内,辨识数据也具有较好的稳定性和准确性,验证了所提方案的可行性和工程应用潜力。

With the threat of weak grid stability brought by the trend of“High Proportion of Renewable Energy and High Proportion of Power Electronic Equipment”to the power grid,in order to achieve real-time monitoring of power grid strength,the online identification of short circuit ratio is necessary.It is needed for many identification methods the design of complex harmonic extraction algorithms or the use of high-precision and high-speed sampling and analysis instruments,which is difficult to operate and costs more.To reduce the difficulty of identifying short circuit ratio,a disturbance response component extraction method based on filtering characteristics and a data outlier group sliding window filtering algorithm were designed,and a 2.5 MW wind turbine grid connection model was built.The simulation results show that the identification error of the short circuit ratio is within 5%,and the identification data also has good stability and accuracy,verifying the feasibility and engineering application potential of the proposed scheme.