基于窄带滤波器和变长数据窗的相量提取算法

LIU Yiqing

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基于窄带滤波器和变长数据窗的相量提取算法

更新时间：2025-08-13

- 基于窄带滤波器和变长数据窗的相量提取算法
- Automation of Electric Power Systems Vol. 39, Issue 8, Pages: 126-132(2015)
- 作者机构：
  
  济南大学自动化与电气工程学院,山东省,济南市,250022
- 作者简介：
- 基金信息：
- DOI：
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- Published：2015
- 稿件说明：
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LIU Yiqing. [J]. Automation of electric power systems, 2015, 39(8): 126-132.
DOI：

LIU Yiqing. [J]. Automation of electric power systems, 2015, 39(8): 126-132. DOI：

摘要

为适应智能变电站全数字化保护系统对相量提取算法的新要求

针对短窗算法滤波性能差而傅里叶算法延时较长且数据窗固定的不足

提出了一种窄带滤波器与变长数据窗相结合的相量提取算法。首先采用窄带滤波器对采样值序列进行带通滤波

并由短窗算法估算滤波器初值

以减小窄带滤波器暂态过程影响

缩短滤波器延时。然后对滤波器输出序列采用基于最小二乘法的变数据窗算法

最终准确提取相量特征。算法充分考虑了智能变电站的特点

实现了可变数据窗的相量提取

在保证滤波精度的同时提高了相量提取速度。数字仿真和动模数据验证表明

该算法可在发生故障后较短时间内准确提取出基波相量

有效提高了智能变电站全数字化保护的速动性和适应性。

Abstract

In order to meet smart substation new demands on phasor extraction algorithm for completely digital relays in face of the poor filtering performance of the short-window algorithm and Fourier algorithm’s long time-delay and fixed data-window

a phasor extracting algorithm with narrow band-pass digital filter (NBDF) and variable data-window combined is proposed. Primarily

the NBDF filters the original sequence of sampled values

with the initial values of NBDF estimated by the short-window algorithm to reduce the impact of NBDF’s transient process and shorten the filter’s time-delay. Then the variable data-window algorithm based on least squares method is applied to the output sequence of NBDF. As a result

the phasor magnitude and phase are acquired. The new algorithm that takes into full account the characteristics of the smart substation mentioned above realizes the phasor extraction of variable data-window

increasing the phasor extracting speed while ensuring filtering precision. Digital simulation and verification by record data show that the proposed algorithm is capable of accurately extracting the fundamental phasor

improving the rapidity and adaptability of completely digital relays in smart substations. This work is supported by Shandong Provincial Natural Science Foundation of China (No. ZR2014EEM039) and Doctoral Scientific Research Foundation of University of Jinan (No. XBS1408).

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Related Institution

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