基于自适应移频滤波的电力系统谐波分析方法

doi:10.19595/j.cnki.1000-6753.tces.230786

Abstract
Figure/Table
References (0)
Related Citation (15)

Download: PDF (2130 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract

With the increasing proportion of various types of nonlinear and impactive loads in the power grid, especially the large-scale integration of new energy sources represented by photovoltaic and wind power, the harmonic issues in the current power system are becoming increasingly severe. Accurately estimating harmonic parameters is not only critical for harmonic control but also an essential basis for power companies and users to evaluate power quality. To achieve accurate and effective detection of harmonic parameters in modern power systems, this paper proposes a power system harmonic analysis method based on adaptive frequency-shift filtering, which estimates harmonic parameters by dynamically and adaptively adjusting frequency deviations.
This method first performs a frequency-shift operation on the original power grid sampled signal based on the nominal frequency ω_nom. Then, considering that it is difficult to completely filter out frequency components other than the target frequency component in a single filtering operation, this paper performs multiple iterations of filtering on the frequency-shift signal. Specifically, the frequency-shift signal is convolved with a p-order self-convolution mean filter (SCMF) to reduce the interference from other frequency components on the target frequency component. After the initial frequency-shift filtering of the power grid harmonic signal, the harmonic angular frequency deviation ?ω, the actual fundamental frequency f_r, and the new frequency-shift function corrected by ?ω can be obtained. Next, according to the desired harmonic order h_s and the frequency-shift function after correction, a second frequency-shift filtering process is carried out, moving the desired harmonic spectral line to the zero frequency position. Finally, the amplitude and phase of the desired harmonic component can be accurately obtained by using the derived formulas. For a power grid sampled signal with length N and using fast convolution for the convolution operation in the algorithm, the time complexity of the proposed algorithm is O(Nlog₂N). Compared with the windowed interpolation FFT algorithm (WIFFT), the time complexity of both algorithms is similar. However, the WIFFT algorithm requires prior determination of fitting coefficients through polynomial fitting. Therefore, the algorithm proposed in this paper is more convenient and straightforward in practical applications, thus offering distinct advantages.
This paper conducted simulation experiments on the algorithm under conditions of weak amplitude harmonic signal, fundamental frequency deviation, noise impact, etc., and also established an actual hardware testing platform. The amplitude relative error and the phase absolute error of the actual measurement results fully meet the requirements of Class A meters in GB/T 14549 “Quality of electric energy supply — Harmonics in public supply network”. Simulation experiments and practical measurement results demonstrate that the proposed method can accurately and effectively detect power system harmonic parameters, showing significant advantages in robustness, adaptability, and real-time performance. Especially for detecting weak amplitude harmonic components, this method exhibits strong applicability. The proposed method can provide new solutions and ideas for the effective and fast analysis of harmonic parameters in complex power grid environments, as well as theoretical and engineering application issues related to electric energy science and accurate metering in the electric power system.

Key words： Power system analysis Power quality Grid harmonics Frequency-shift filtering

Received: 05 June 2023

PACS:

TM933

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Li Jianmin
	Cao Yuanyuan
	Yao Wenxuan
	Liang Chengbin
	Yu Jiaqi

Cite this article:

Li Jianmin,Cao Yuanyuan,Yao Wenxuan等. Power System Harmonic Analysis Method Based on Adaptive Frequency-shift Filtering[J]. Transactions of China Electrotechnical Society, 0, (): 230786-.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.230786 OR https://dgjsxb.ces-transaction.com/EN/Y0/V/I/230786

[1] Ma Xiaoyang, Yang Qiuling, Chen Chang, et al.Harmonic and interharmonic analysis of mixed dense frequency signals[J]. IEEE Transactions on Industrial Electronics, 2021, 68(10): 10142-10153.
[2] Langella R, Testa A, Meyer J, et al.Experimental-based evaluation of PV inverter harmonic and interharmonic distortion due to different operating conditions[J]. IEEE Transactions on Instrumentation and Measurement, 2016, 65(10): 2221-2233.
[3] 杨逸帆, 赵兵兵, 康迪, 等. 基于改进希尔伯特-黄变换的电力系统谐波检测系统设计[J]. 电气技术, 2022, 23(5): 9-17.
Yang Yifan, Zhao Bingbing, Kang Di, et al.Design of power system harmonic detection system based on improved Hilbert-Huang transform[J]. Electrical Engineering, 2022, 23(5): 9-17.
[4] Memije D, Carranza O, Rodríguez J J, et al.Inverter harmonic perturbations rejection in renewable energy conversion systems applying a super-twisting algorithm[J]. IET Renewable Power Generation, 2021, 15(7): 1483-1497.
[5] 叶宗彬, 侯波, 张延澳, 等. 一种三相对称系统快速谐波检测算法[J]. 电工技术学报, 2023, 38(2): 510-522.
Ye Zongbin, Hou Bo, Zhang Yan'ao, et al. A fast harmonic detection algorithm for three-phase symmetric systems[J]. Transactions of China Electrotechnical Society, 2023, 38(2): 510-522.
[6] Louis A, Ledwich G, Walker G, et al.Measurement sensitivity and estimation error in distribution system state estimation using augmented complex Kalman filter[J]. Journal of Modern Power Systems and Clean Energy, 2020, 8(4): 657-668.
[7] Xia Xin, Li Chaoshun, Ni Wei.Dominant low-frequency oscillation modes tracking and parameter optimisation of electrical power system using modified Prony method[J]. IET Generation, Transmission & Distribution, 2017, 11(17): 4358-4364.
[8] Lin F J, Lu K C, Ke Tinghan.Probabilistic Wavelet Fuzzy Neural Network based reactive power control for grid-connected three-phase PV system during grid faults[J]. Renewable Energy, 2016, 92: 437-449.
[9] Xiao Liye, Shao Wei, Yu Mengxia, et al.Research and application of a hybrid wavelet neural network model with the improved cuckoo search algorithm for electrical power system forecasting[J]. Applied Energy, 2017, 198: 203-222.
[10] Chang G W, Lin Y L, Liu Y J, et al.A hybrid approach for time-varying harmonic and interharmonic detection using synchrosqueezing wavelet transform[J]. Applied Sciences, 2021, 11(2): 752.
[11] 黄冬梅, 唐志涛, 张晋轩, 等. 基于FFT的电力谐波分析方法[J]. 电工技术, 2022(20): 213-216.
Huang Dongmei, Tang Zhitao, Zhang Jinxuan, et al.Power harmonic analysis based on FFT[J]. Electric Engineering, 2022(20): 213-216.
[12] 王保帅, 肖勇, 胡珊珊, 等. 适用于非整数次幂的高精度混合基FFT谐波测量算法[J]. 电工技术学报, 2021, 36(13): 2812-2820, 2843.
Wang Baoshuai, Xiao Yong, Hu Shanshan, et al.High precision mixed radix FFT algorithm for harmonic measurement under non-integer power sequence[J]. Transactions of China Electrotechnical Society, 2021, 36(13): 2812-2820, 2843.
[13] Xi Yanhui, Tang Xin, Li Zewen, et al.Harmonic estimation in power systems using an optimised adaptive Kalman filter based on PSO-GA[J]. IET Generation, Transmission & Distribution, 2019, 13(17): 3968-3979.
[14] 杨挺, 武金成, 袁博. 谐波和间谐波检测的压缩感知恢复算法[J]. 中国电机工程学报, 2015, 35(21): 5475-5482.
Yang Ting, Wu Jincheng, Yuan Bo.The restoration algorithm of compressed sensing to detect harmonic and inter-harmonic[J]. Proceedings of the CSEE, 2015, 35(21): 5475-5482.
[15] Tang Yuanhong, Hu Weihao, Cao Di, et al.Artificial intelligence-aided minimum reactive power control for the DAB converter based on harmonic analysis method[J]. IEEE Transactions on Power Electronics, 2021, 36(9): 9704-9710.
[16] 张俊敏, 刘开培, 汪立, 等. 基于主瓣宽度多谱线插值的高精度快速谐波分析算法[J]. 电工技术学报, 2018, 33(增刊1): 121-128.
Zhang Junmin, Liu Kaipei, Wang Li, et al.A precise and rapid algorithm for harmonic analysis based on multi-spectrum-line in main lobe width interpolation FFT[J]. Transactions of China Electrotechnical Society, 2018, 33(S1): 121-128.
[17] Wen He, Guo Siyu, Teng Zhaosheng, et al.Frequency estimation of distorted and noisy signals in power systems by FFT-based approach[J]. IEEE Transactions on Power Systems, 2014, 29(2): 765-774.
[18] Wen He, Teng Zhaosheng, Wang Yong, et al.Spectral correction approach based on desirable sidelobe window for harmonic analysis of industrial power system[J]. IEEE Transactions on Industrial Electronics, 2013, 60(3): 1001-1010.
[19] 吴禹, 唐求, 滕召胜, 等. 基于改进S变换的电能质量扰动信号特征提取方法[J]. 中国电机工程学报, 2016, 36(10): 2682-2689.
Wu Yu, Tang Qiu, Teng Zhaosheng, et al.Feature extraction method of power quality disturbance signals based on modified S-transform[J]. Proceedings of the CSEE, 2016, 36(10): 2682-2689.
[20] 陈至豪, 王立德, 王冲, 等. 基于组合余弦优化窗四谱线插值FFT的电力谐波分析方法[J]. 电网技术, 2020, 44(3): 1105-1113.
Chen Zhihao, Wang Lide, Wang Chong, et al.An approach for electrical harmonic analysis based on optimized composite cosine window four-spectrum-line interpolation FFT[J]. Power System Technology, 2020, 44(3): 1105-1113.
[21] 周西峰, 赵蓉, 郭前岗. Blackman-Harris窗的插值FFT谐波分析与应用[J]. 电测与仪表, 2014, 51(11): 81-85.
Zhou Xifeng, Zhao Rong, Guo Qiangang.Blackman-harris window based interpolation FFT harmonic analysis and its application[J]. Electrical Measurement & Instrumentation, 2014, 51(11): 81-85.
[22] Li Jianmin, Cao Yuanyuan, Zhang Xuhui, et al.An accurate harmonic parameter estimation method based on Slepian and Nuttall mutual convolution window[J]. Measurement, 2021, 174: 109027.
[23] 吴超凡, 陈隆道. 应用于电力谐波分析的改进相位差校正法[J]. 电工技术学报, 2017, 32(7): 158-164.
Wu Chaofan, Chen Longdao.Improved phase difference correction method applied to power harmonic analysis[J]. Transactions of China Electrotechnical Society, 2017, 32(7): 158-164.
[24] 贾清泉, 杨晓雯, 宋知用. 一种电力系统谐波信号的加窗频移算法[J]. 中国电机工程学报, 2014, 34(10): 1631-1640.
Jia Qingquan, Yang Xiaowen, Song Zhiyong.A window frequency shift algorithm for power system harmonic analysis[J]. Proceedings of the CSEE, 2014, 34(10): 1631-1640.
[25] 叶宗彬, 侯波, 张延澳, 等. 一种三相对称系统快速谐波检测算法[J]. 电工技术学报, 2023, 38(2): 510-522.
Ye Zongbin, Hou Bo, Zhang Yan'ao, et al. A fast harmonic detection algorithm for three-phase symmetric systems[J]. Transactions of China Electrotechnical Society, 2023, 38(2): 510-522.
[26] 吴建章, 梅飞, 陈畅, 等. 基于经验小波变换的电力系统谐波检测方法[J]. 电力系统保护与控制, 2020, 48(6): 136-143.
Wu Jianzhang, Mei Fei, Chen Chang, et al.Harmonic detection method in power system based on empirical wavelet transform[J]. Power System Protection and Control, 2020, 48(6): 136-143.
[27] Yao Wenxuan, Teng Zhaosheng, Tang Qiu, et al.Measurement of power system harmonic based on adaptive Kaiser self-convolution window[J]. IET Generation, Transmission & Distribution, 2016, 10(2): 390-398.
[28] 李建闽, 滕召胜, 吴言, 等. 基于移频滤波的频率测量方法[J]. 中国电机工程学报, 2018, 38(3): 762-769.
Li Jianmin, Teng Zhaosheng, Wu Yan, et al.Frequency measurement algorithm based on frequency shift and filtering[J]. Proceedings of the CSEE, 2018, 38(3): 762-769.
[29] Shuai Zhikang, Zhang Junhao, Tang Lu, et al.Frequency shifting and filtering algorithm for power system harmonic estimation[J]. IEEE Transactions on Industrial Informatics, 2019, 15(3): 1554-1565.