基于多数据点组合加权的电力系统频率检测算法

Frequency Detection Algorithm for Power Systems Based on Combined Weighting of Multiple Data Points

中文关键词:电力系统  频率检测  牛顿三次插值  牛顿迭代法  最优组合加权

keywords:power system  frequency detection  Newton’s cubic interpolation  Newton’s iterative method  optimal combined weighting

中文摘要:随着新能源在电力系统中所占比例的不断增长，系统的惯量逐渐减少，导致频率变化更为剧烈。针对这一问题，提出了一种快速并且高精度的频率测量算法。该算法将原始信号经过低通滤波器滤波后，对零点附近的8个数据点进行研究，分别计算它们所对应的频率值。为了提高频率测量的精确度，将8个数据点所对应频率估计值进行最优组合加权，求取电力系统频率测量值。在对各个数据点进行频率计算的时候，采用牛顿三次插值进行拟合。仿真实验结果表明，所提算法在信号频率偏移、信号含噪声、信号幅值和相角动态调制的条件下均具有较好的运行速度及测量精度。

Abstract:With the continuous increase in the proportion of new energy in power systems，the system inertia is gradually reduced，leading to more drastic frequency fluctuations. To address this problem，a fast and high-precision frequency measurement algorithm is proposed. First，the original signal is filtered by a low-pass filter，then eight data points near the zero crossing are selected for analysis，and their corresponding frequency values are calculated respectively. To improve the accuracy of frequency measurement，the optimal combined weighting of the eight frequency estimates corresponding to the data points is performed to obtain the final frequency measurement value of the power system. Newton's cubic interpolation is adopted for fitting when calculating the frequency of each data point. Simulation results show that the proposed algorithm has excellent operation speed and measurement accuracy under the conditions of signal frequency offset，signal with noise，and dynamic modulation of signal amplitude and phase angle.