scholarly journals Harmonic Frequency Estimation Algorithm Based on MSWF in Power System

2015 ◽  
Vol 9 (1) ◽  
pp. 524-529
Author(s):  
Cao Zhe ◽  
Sun Xiangwen ◽  
Niu Xinwen
Keyword(s):  
Computational Complexity ◽  
Power System ◽  
Frequency Estimation ◽  
Recursive Algorithm ◽  
Wiener Filter ◽  
Estimation Algorithm ◽  
Music Algorithm ◽  
Harmonic Frequency ◽  
Multi Stage ◽  
Data Volume

This paper pointed out the disadvantage of harmonic frequency estimation algorithm in current power system, presented the MUSIC (multiple signal classification)-based harmonic frequency estimation algorithm in power system, and analyzed the computational complexity of the MUSIC algorithm. In order to reduce the computational complexity of conventional MUSIC algorithm and to increase the real-time characteristic of harmonic frequency estimation algorithm, we combined the multi-stage wiener filter (MSWF) recursive algorithm and MUSIC algorithm so as to avoid the subspace decomposition process of the conventional MUSIC algorithm, thus realizing the purpose of significantly reducing the computational complexity of the MUSIC algorithm. Through theoretical analysis and simulation experiments, we find that the algorithm proposed in this paper is of excellent resolution characteristic, and less dependent on data volume.

Harmonic Estimation Algorithm for Power System Based on Improved MUISC and Linear Neural Networks

2015 ◽  
Vol 9 (1) ◽  
pp. 445-451 ◽  
Author(s):  
Sun Ligong Ligong ◽  
Sun Xiangwen ◽  
Xiang Fei
Keyword(s):  
Neural Network ◽  
Power System ◽  
Frequency Estimation ◽  
Wiener Filter ◽  
Estimation Algorithm ◽  
Estimation Accuracy ◽  
Music Algorithm ◽  
Multiple Signal Classification ◽  
Harmonic Phase ◽  
Linear Neural Network

The paper proposes harmonic estimation algorithm for power system based on Multiple Signal Classification (MUSIC) and linear neural network because of the insufficiency of harmonic frequency estimation algorithm. The conventional MUSIC algorithm has the advantage of higher estimation accuracy, while the disadvantage is that the computational complexity is high and it cannot estimate the harmonic phase and amplitude. In the paper, a new harmonic estimation algorithm for power system is constructed with combining the MUSIC algorithm, the multistage Wiener filter (MSWF) and linear neural network. Theoretic analysis and simulation experiments show that the requirement to data is relatively low, and has good harmonic estimation accuracy and reliability.

scholarly journals Harmonic Frequency Estimation Algorithm based on ESPRIT and MSWF in Power System

2015 ◽  
Vol 9 (1) ◽  
pp. 518-523 ◽  
Author(s):  
Sun Xiangwen ◽  
Cao Zhe ◽  
Tian Wei
Keyword(s):  
Power System ◽  
Simulation Experiment ◽  
Frequency Estimation ◽  
Wiener Filter ◽  
Estimation Algorithm ◽  
Frequency Resolution ◽  
Harmonic Frequency ◽  
Fast Estimation ◽  
Multistage Wiener Filter ◽  
Esprit Algorithm

This paper points out the deficiency in the current harmonic frequency estimation algorithm in power system. In order to improve the accuracy of detection and reduce the computational complexity, the study combined the ESPRIT algorithm with multistage Wiener filter (MSWF) recurrence to achieve fast estimation of harmonic frequency. Theoretical analysis and simulation experiment show that the algorithm had relatively low requirement for the amount of data, and demonstrated good frequency resolution characteristics and anti-jamming capability, which made it ideally suitable for harmonic analysis in power system.

A Unitary-UCA-Root-MUSIC Algorithm Based on MSWF

2014 ◽  
Vol 610 ◽  
pp. 339-344
Author(s):  
Qiang Guo ◽  
Yun Fei An
Keyword(s):  
Computer Simulation ◽  
Computational Complexity ◽  
Real Time ◽  
Unitary Transformation ◽  
Wiener Filter ◽  
Doa Estimation ◽  
Signal Subspace ◽  
Music Algorithm ◽  
Multi Stage ◽  
Simulation Results

A UCA-Root-MUSIC algorithm for direction-of-arrival (DOA) estimation is proposed in this paper which is based on UCA-RB-MUSIC [1]. The method utilizes not only a unitary transformation matrix different from UCA-RB-MUSIC but also the multi-stage Wiener filter (MSWF) to estimate the signal subspace and the number of sources, so that the new method has lower computational complexity and is more conducive to the real-time implementation. The computer simulation results demonstrate the improvement with the proposed method.

Harmonic Frequency Estimation Based on Modified-MUSIC Algorithm in Power System

2015 ◽  
Vol 9 (1) ◽  
pp. 38-42 ◽  
Author(s):  
Xiangwen Sun ◽  
Ligong Sun
Keyword(s):  
Frequency Estimation ◽  
Estimation Method ◽  
Super Resolution ◽  
Small Data ◽  
Music Algorithm ◽  
Harmonic Frequency ◽  
Multiple Signal Classification ◽  
Analysis Techniques ◽  
Resolution Algorithm ◽  
Data Length

This paper presents a new harmonics frequency estimation method. Unlike the conventional harmonic frequency estimation method (fast Fourier transform), the new algorithm is based on spectrum analysis techniques often used to estimate the direction of angle; the most popular is the multiple signal classification (MUSIC) algorithm. The drawbacks of MUSIC algorithm are concluded. Improved-MUSIC approximation algorithm is introduced and compared with FFT based on algorithm for harmonic frequency estimation. Theoretical analysis and simulations show this algorithm is a super- resolution algorithm with small data length.

Power System Frequency Estimation Algorithm for Electric Energy Metering of Nonlinear Loads

2012 ◽  
Vol 19 (2) ◽  
pp. 307-320
Author(s):  
Zhang Peng ◽  
Li Hong-Bin
Keyword(s):  
Power System ◽  
Frequency Estimation ◽  
Electric Energy ◽  
Estimation Algorithm ◽  
Discrete Wavelet ◽  
Monitoring And Control ◽  
Nonlinear Loads ◽  
Nonlinear Load ◽  
Energy Metering ◽  
System Frequency

Power System Frequency Estimation Algorithm for Electric Energy Metering of Nonlinear LoadsIn this paper, a discrete wavelet transform (DWT) based approach is proposed for power system frequency estimation. Unlike the existing frequency estimators mainly used for power system monitoring and control, the proposed approach is developed for fundamental frequency estimation in the field of energy metering of nonlinear loads. The characteristics of a nonlinear load is that the power signal is heavily distorted, composed of harmonics, inter-harmonics and corrupted by noise. The main idea is to predetermine a series of frequency points, and the mean value of two frequency points nearest to the power system frequency is accepted as the approximate solution. Firstly the input signal is modulated with a series of modulating signals, whose frequencies are those frequency points. Then the modulated signals are decomposed into individual frequency bands using DWT, and differences between the maximum and minimum wavelet coefficients in the lowest frequency band are calculated. Similarities among power system frequency and those frequency points are judged by the differences. Simulation results have proven high immunity to noise, harmonic and inter-harmonic interferences. The proposed method is applicable for real-time power system frequency estimation for electric energy measurement of nonlinear loads.

A Novel Non-Data-Aided Frequency Estimation Algorithm for M-PSK Signals

2013 ◽  
Vol 756-759 ◽  
pp. 3109-3113
Author(s):  
Qing Hua Tian ◽  
Xin Man ◽  
Sheng Zeng
Keyword(s):  
Computational Complexity ◽  
Carrier Frequency ◽  
Frequency Estimation ◽  
Estimation Algorithm ◽  
New Method ◽  
Estimation Accuracy ◽  
Step Factor ◽  
Carrier Frequency Estimation ◽  
Estimation Range

This paper deals with the problem of carrier frequency estimation for MPSK symbols. We present a novel non-data-aided method by introducing a step factor into an earlier estimation algorithm to reduce the computational complexity with little loss of the estimation accuracy. We also make some comparisons with earlier algorithms. From the results of simulations, we make the conclusion that the new method can separate the estimation range and the estimation accuracy, and avoid the weakness of reaching large estimation range at the expense of estimation accuracy.

scholarly journals A Real-Time Harmonic Extraction Approach for Distorted Grid

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2245
Author(s):  
Po Li ◽  
Xiang Li ◽  
Jinghui Li ◽  
Yimin You ◽  
Zhongqing Sang
Keyword(s):  
Power System ◽  
Real Time ◽  
Frequency Estimation ◽  
Harmonic Component ◽  
Estimation Algorithm ◽  
Phase Variable ◽  
Current Frequency ◽  
Zero Crossing ◽  
Grid Current ◽  
Harmonic Extraction

Harmonic interference is a major hazard in the current power system that affects power quality. How to extract harmonics quickly and accurately is the premise to ensure the sustainable operation of power system, which is particularly important in the field of new energy power generation. In this paper, a harmonic extraction method based on a time-varying observer is proposed. Firstly, a frequency estimation algorithm is used to estimate the power grid current frequency, which can estimate the frequency in real time. Then, applying the zero-crossing detection method to convert the frequency into a phase variable. Finally, using the phase variable and integral current signal as input, a observer is modeled to extract each order harmonic component. The proposed method is evaluated on a FGPA test platform, which shows that the method can extract the harmonic components of the grid current and converge within 80 ms even in the presence of grid distortions. In the verification case, the relative errors of the 1st, 5th, 7th and 11th harmonics are 0.005%, −0.003%, 0.251% and 0.620%, respectively, which are sufficiently small.

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