基于改进泰勒加权最小二乘法的相量测量算法

大部分相量测量算法将信号相量作为一个静态模型，因此对电网中经常发生的电压幅值和相角波动特别敏感。基于标准频率下动态相量模型的泰勒加权最小二乘法(Taylor Weighted Least Squares, TWLS)不仅提供了相量值，还提供了相量导数值，可以提高对电网动态状况的监测。在此基础上，提出了一种基于基波频率值的改进泰勒加权最小二乘法。首先用非线性最小二乘法得到基波频率值。然后介绍了基于测量基波频率值的改进泰勒加权最小二乘法推导过程，并对该算法所涉及的窗函数、数据窗长度和泰勒多项式阶数进行分析选择。最后采用不同的信号模型和实际数据来检验算法的性能。仿真结果表明:提出的改进泰勒加权最小二乘法的测量精度满足要求。

A phasor measurement algorithm based on improved Taylor weighted least squares

Most phasor measurement algorithms consider signal phasors as a steady-state model, so they are very sensitive to voltage amplitude and angle fluctuations that often occur in modern power grids. Taylor Weighted Least Squares (TWLS) algorithm relies on a dynamic phasor model at nominal frequency. The algorithm not only provide the phasor values but also give its derivatives to improve the dynamic monitoring of the power grid. On this basis, an improved TWLS method based on fundamental frequency is proposed. First, the fundamental frequency is obtained by nonlinear least squares method. Then, the derivation process of the TWLS algorithm based on the calculated fundamental frequency is introduced, and the window function, the length of the data window and Taylor polynomial order involved in the algorithm are analyzed and selected. Finally, different signal models and actual data are used to test the performance of the algorithm. The simulation results show that the accuracy of the improved TWLS algorithm meets the requirements of synchronized phasor measurement. This work is supported by National Natural Science Foundation for Young Scholars (No. 51505317) and Natural Science Foundation of Shanxi Province (No. 201601D102039).