ISSN 0253-2778

CN 34-1054/N

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Power measurement based on VSLMS improved adaptive filters

  • 1.

    Department of Automation, University of Science and Technology of China, Hefei 230027, China

  • 2.

    State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230027, China

  • 3.

    Department of Automation, Zhejiang University of Technology, Hangzhou 310014, China

Funds:  Supported by the National Natural Science Foundation of China( 61422307, 61304048 and 61174061), the Scientific Research Staring Foundation for the Returned Overseas Chinese Scholars of Ministry of Education of China and the National High-tech R&D Program of China (863)(2014AA06A503). the Youth Innovation Promotion Association,Chinese Academy of Sciences and National Youth Top Talent Support of National High-Level Personnel of Special Support Program.
Cite this:
https://doi.org/10.3969/j.issn.0253-2778.2015.10.008
More Information
  • Author Bio:

    QIAN QI, male, born in 1989.Research field: Control theory.E-mail:qqianl@mail.ustc.edu.cn

  • Corresponding author: Kang Yu
  • Received Date: 06 March 2015
  • Accepted Date: 16 April 2015
  • Rev Recd Date: 16 April 2015
  • Publish Date: 30 October 2015
    Abstract

  • Abstract

    A new algorithm is proposed to detect and extract in real-time signals with fundamental and harmonic wave components in the power grid, which is applicable to power measurement. The proposed method is based on the concept of adaptive filter, and adaptively decomposes the measured power signal into its constituting components, resulting in a fast convergence rate. The fundamental and harmonic wave components in the power grid can be decomposed into a series of sinusoidal signals. The frequency of the power grid is measured by energy operator. A model of voltage and current wave in the power grid is constructed, a new step-size LMS algorithm for improving the adaptive filter is proposed and the stability of the proposed method is discussed. The effectiveness of the proposed method is demonstrated by simulation examples.

    Abstract

    A new algorithm is proposed to detect and extract in real-time signals with fundamental and harmonic wave components in the power grid, which is applicable to power measurement. The proposed method is based on the concept of adaptive filter, and adaptively decomposes the measured power signal into its constituting components, resulting in a fast convergence rate. The fundamental and harmonic wave components in the power grid can be decomposed into a series of sinusoidal signals. The frequency of the power grid is measured by energy operator. A model of voltage and current wave in the power grid is constructed, a new step-size LMS algorithm for improving the adaptive filter is proposed and the stability of the proposed method is discussed. The effectiveness of the proposed method is demonstrated by simulation examples.
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    • References(15)
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    Pang H, Li D X, Zu Y X, et al. An improved algorithm for harmonic analysis of power system using FFT technique[J]. Proceedings of the CSEE, 2003, 23(6): 50-54.
    [2]
    Zhang F S, Geng Z X, Yuan W. The algorithm of interpolating windowed FFT for harmonic analysis of electric power system[J]. IEEE Transactions on Power Delivery, 2001, 16(2): 160-164.
    [3]
    Mojiri M, Karimi-Ghartemani M, Bakhshai A. Time-domain signal analysis using adaptive notch filter[J]. IEEE Transactions on Signal Processing, 2007, 55(1): 85-93.
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    Yazdekhasti A, Mojiri M. A method for harmonic extraction from power systems signals based on adaptive notch filter[J]. Advances in Computational Mathematics and its Applications, 2012, 1(1): 40-46.
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    Chien W C, Lin C M, Singh P K, et al. MMIC compact filters with third harmonic suppression for V-band applications[J]. Microwave and Wireless Components Letters, 2011, 21(6): 295-297.
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    郑军, 颜文俊, 诸静. 基于尺度滤波与小波去噪的PID继电整定[J]. 控制与决策, 2005, 20(7): 811-814,833.
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    张玉璘, 陈伟民, 杨建春, 等. 小波变换自适应滤波器及其在主动噪声控制中的应用[J].控制与决策, 2002, 17(1): 107-110.
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    倪元敏, 张晓冰. 畸变信号条件下电能合理计量方法探讨[J]. 电力系统自动化, 2008, 32(17): 88-91.
    Ni Y M, Zhang X B. Research on a new method of rational electric energy measurement under the distorted signals condition [J]. Automation of Electric Power Systems, 2008, 32(17): 88-91.
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    Wakileh G J. 电力系统谐波--基本原理、分析方法和滤波器设计[M]. 徐证译, 北京: 机械工业出版社, 2003.
    [14]
    Maragos P, Kaiser J F, Quatieri T F. Energy separation in signal modulations with application to speech analysis [J]. IEEE Transactions on Signal Processing, 1993, 41(10): 3024-3051.
    [15]
    Sristi P, Lu W S, Antoniou A. A new variable-step-size LMS algorithm and its application in subband adaptive filtering for echo cancellation[J]. IEEE International Symposium on Circuits and Systems, 2012, 2: 721-724.
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    [1]
    庞浩，李东霞，俎云霄，等. 应用FFT进行电力系统谐波分析的改进算法[J].中国电机工程学报，2003，23(6): 50-54.
    Pang H, Li D X, Zu Y X, et al. An improved algorithm for harmonic analysis of power system using FFT technique[J]. Proceedings of the CSEE, 2003, 23(6): 50-54.
    [2]
    Zhang F S, Geng Z X, Yuan W. The algorithm of interpolating windowed FFT for harmonic analysis of electric power system[J]. IEEE Transactions on Power Delivery, 2001, 16(2): 160-164.
    [3]
    Mojiri M, Karimi-Ghartemani M, Bakhshai A. Time-domain signal analysis using adaptive notch filter[J]. IEEE Transactions on Signal Processing, 2007, 55(1): 85-93.
    [4]
    刘欢，褚建新，俞万能. 改进型自适应陷波器电力系统频率估计方法[J]. 上海海事大学学报, 2007, 28(3): 24-27.
    Liu H, Chu J X, Yu W N, Accurate estimation of power system frequency using a modified adaptive notch filter[J]. Joumal of Shanghai Maritime University, 2007, 28(3): 24-27.
    [5]
    Yazdekhasti A, Mojiri M. A method for harmonic extraction from power systems signals based on adaptive notch filter[J]. Advances in Computational Mathematics and its Applications, 2012, 1(1): 40-46.
    [6]
    Chien W C, Lin C M, Singh P K, et al. MMIC compact filters with third harmonic suppression for V-band applications[J]. Microwave and Wireless Components Letters, 2011, 21(6): 295-297.
    [7]
    薛蕙, 罗红. 小波变换与傅里叶变换相结合的暂态谐波分析方法[J]. 中国农业大学学报, 2007, 12(6): 89-92.
    Xue H, Luo H. Transient harmonic analysis algorithm using wavelet transform and Fourier transform [J]. Journal of China Agricultural University, 2007, 12(6): 89-92.
    [8]
    Nguyen N, Milanfar P. A wavelet-based interpolation restoration method for superresolution (wavelet superresolution)[J]. Circuits, Systems and Signal Processing, 2000, 19(4): 321-338.
    [9]
    Stephanakis I M, Kollias S. Optimal wavelet filter banks for regularized restoration of noisy images [J]. Circuits, Systems and Signal Processing, 2000, 19(2): 99-119.
    [10]
    郑军, 颜文俊, 诸静. 基于尺度滤波与小波去噪的PID继电整定[J]. 控制与决策, 2005, 20(7): 811-814,833.
    Zheng J, Yan W J, Zhu J. Relay auto-turning for PID control based on scale filter and wavelet denoising [J]. Control and Decision, 2005, 20(7): 811-814,833.
    [11]
    张玉璘, 陈伟民, 杨建春, 等. 小波变换自适应滤波器及其在主动噪声控制中的应用[J].控制与决策, 2002, 17(1): 107-110.
    Zhang Y L, Chen W M, Yang J C, et al. Wavelet transformation adaptive filter and its application in active noise control [J]. Control and Decision, 2002, 17(1): 107-110.
    [12]
    倪元敏, 张晓冰. 畸变信号条件下电能合理计量方法探讨[J]. 电力系统自动化, 2008, 32(17): 88-91.
    Ni Y M, Zhang X B. Research on a new method of rational electric energy measurement under the distorted signals condition [J]. Automation of Electric Power Systems, 2008, 32(17): 88-91.
    [13]
    Wakileh G J. 电力系统谐波--基本原理、分析方法和滤波器设计[M]. 徐证译, 北京: 机械工业出版社, 2003.
    [14]
    Maragos P, Kaiser J F, Quatieri T F. Energy separation in signal modulations with application to speech analysis [J]. IEEE Transactions on Signal Processing, 1993, 41(10): 3024-3051.
    [15]
    Sristi P, Lu W S, Antoniou A. A new variable-step-size LMS algorithm and its application in subband adaptive filtering for echo cancellation[J]. IEEE International Symposium on Circuits and Systems, 2012, 2: 721-724.
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