Harmonic Current Detection Based on Improved LMS Algorithm

Qiankun LI; Yili LIU; Shengxing LIU

doi:10.16513/j.2096-2185.DE.2207502

TSINGHUA JOURNALS HOME

Source Journal for Chinese Scientific and Technical Papers and Citations

RCCSE Chinese Core Academic Journals

Classification Catalogue of High Quality Scientific Journals in the field of Energy and Power

Classification Catalogue of High Quality Scientific Journals in Coal Field

PDF(2329 KB)

Distributed Energy ›› 2022, Vol. 7 ›› Issue (5) : 9-16. DOI: 10.16513/j.2096-2185.DE.2207502

Basic Research

Harmonic Current Detection Based on Improved LMS Algorithm

Author information +

History +

Abstract

In order to improve the detection effect of harmonic current and enable the active filter (APF) to better eliminate harmonics, this paper firstly uses a fixed-step minimum least mean square (LMS) algorithm on the basis of APF and embeds a low-pass filter. Then use the sparrow search algorithm (SSA) to improve the filtering parameters, and then change the load parameter value to verify that the improved LMS algorithm is also applicable under different load values, and finally by using Matlab a simulation model was built, and the three different methods of fixed-step LMS algorithm, SSA algorithm, and particle swarm algorithm (PSO) were compared in the model to improve the simulation effect of filtering parameters. The simulation results show that the SSA algorithm is used to optimize the parameters. It can make the current flowing through the power grid reach the level of only the fundamental current, and reduce the total harmonic distortion (THD) of the current to less than 5%, which meets the IEEE standard, reduces the harmonic content of the current, and makes the system more stable. The applicability and feasibility of the method are also shown.

Key words

harmonic detection / least mean square (LMS) algorithm / sparrow search algorithm (SSA) / fundamental current

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Qiankun LI , Yili LIU , Shengxing LIU. Harmonic Current Detection Based on Improved LMS Algorithm[J]. Distributed Energy Resources. 2022, 7(5): 9-16 https://doi.org/10.16513/j.2096-2185.DE.2207502

References

List( Publishing order | Descend order by publishing year | Descend order by cited within ) Chart analysis

[1]	杨立军，毛宇阳，杨志，等. 高性能谐波电流检测及控制方法[J]. 电力电子技术，2019, 53(8): 1-3. YANG Lijun, MAO Yuyang, YANG Zhi, et al. A high-performance harmonic current detection method and control strategy[J]. Power Electronics, 2019, 53(8): 1-3. Cited in this article [1]

[2]	张建忠，耿治，徐帅，等. 一种有源电力滤波器的改进自适应谐波检测算法[J]. 电工技术学报，2019, 34(20): 4323-4333. ZHANG Jianzhong, GENG Zhi, XU Shuai, et al. An improved adaptive harmonic detection algorithm for active power filter[J]. Transactions of China Electrotechnical Society, 2019, 34(20): 4323-4333. Cited in this article [1]

[3]	王清亮，应欣峰，宋曦，等. 基于i_p-i_q法的改进谐波电流检测方法[J]. 电子测量技术，2022, 45(6): 72-78. WANG Qingliang, YING Xinfeng, SONG Xi, et al. Improved harmonic current detection method based on i_p-i_q method[J]. Electronic Measurement Technology, 2022, 45(6): 72-78. Cited in this article [1]

[4]	李翔. 有源电力滤波器谐波检测与抑制方法研究[D]. 陕西：西安科技大学，2020. LI Xiang. Research on harmonic detection and suppression method of active power filter [D]. Shaanxi: Xi'an University of Science and Technology, 2020. Cited in this article [1]

[5]	彭咏龙，张坤锋，李亚斌，等. 基于自适应算法的谐波检测方法研究[J]. 电测与仪表，2018, 5(55): 6-9. PENG Yonglong, ZHANG Kunfeng, LI Yabin, et al. Research on harmonic detection method based on adaptive algorithm[J]. Electrical Measurement and Instrumentation, 2018, 5(55): 6-9. Cited in this article [1]

[6]	CHAUDHARI K R, TRIVEDI T A. Analysis on control strategy of shunt active power filter for three-phase three-wire system[C]//2014 IEEE PES Transmission & Distribution Conference and Exposition-Latin America (PES T&D-LA). 2014: 1-6. Cited in this article [1]

[7]	刘倩倩. 自适应滤波算法及其在电力谐波检测的应用[D]. 成都：西南交通大学，2018. LIU Qianqian. Adaptive filtering algorithm and its application in power harmonic detection [D]. Chengdu: Southwest Jiaotong University, 2018. Cited in this article [1]

[8]	SINGH B, SOLANKI J. An implementation of an adaptive control algorithm for a three-phase shunt active filter[J]. IEEE Transactions on Industrial Electronics, 2009, 56(8): 2811-2820. Cited in this article [1]

[9]	叶朋，张东洋，李广剑，等. 基于改进LMS算法的引信自适应去噪声研究[J]. 火力与指挥控制，2020, 45(10): 63-66. YE Peng, ZHANG Dongyang, LI Guangjian, et al. Adaptive noise cancellation in fuze based on the improved LMS algorithm[J]. Fire Control & Command Control, 2020, 45(10): 63-66. Cited in this article [1]

[10]	白群，赵闻蕾. 基于自适应滤波算法的牵引网谐波电流检测[J]. 大连交通大学学报，2021, 6(42): 111-115. BAI Qun, ZHAO Wenlei. An Improved variable step size LMS adaptive filtering algorithm[J]. Journal of Dalian Jiaotong University, 2021, 6(42): 111-115. Cited in this article [1]

[11]

张展，王维，史松林，等. 基于改进双曲正切函数的LMS谐波电流检测算法[J]. 武汉大学学报(工学版), 2020, 53(12): 1085-1090.

ZHANG

Zhan

, WANG

Wei

, SHI

Songlin

, et al. LMS harmonic current detection algorithm based on improved hyperbolic tangent function[J]. Engineering Journal of Wuhan University, 2020, 53(12): 1085-1090.

Cited in this article [1]

[12]	PERESADA S, ZAICHENKO Y, KOVBASA S, et al. Adaptive current control for shunt active power filters[C]//2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO), 2018: 598-604. Cited in this article [1]

[13]	ZHOU Y, SHAO W, CHENG Y, et al. An improved LMS harmonic current detection algorithm[C]//2021 3rd Asia Energy and Electrical Engineering Symposium (AEEES), 2021: 50-54. Cited in this article [1]

[14]	王亚军. 基于变步长LMS算法的谐波电流检测与治理研究[D]. 大庆：东北石油大学，2021. WANG Yajun. Research on harmonic current detection and control based on variable step size LMS algorithm [D]. Daqing: Northeast Petroleum University, 2021. Cited in this article [1]

[15]	XUE J K, SHEN B. A novel swarm intelligence optimization approach: sparrow search algorithm[J]. Systems Science & Control Engineering, 2020, 8(1), 22-34. Cited in this article [1]

[16]

邵文权，徐嘉鹏，卫晓辉，等. 采用PI＋重复控制策略的配电网有源电流消弧方案[J]. 西安工程大学学报，2022, 36(3): 1-8.

SHAO

Wenquan

, XU

Jiapeng

, WEI

Xiaohui

, at al. A strategy active current arc suppression scheme using PI and repetitive control for distribution networks[J]. Journal of Xi'an Polytechnic University, 2022, 36(3): 1-8.

Cited in this article [1]

[17]	李鹏，丁倩雯. 基于麻雀算法优化的OSTU分割算法[J]. 电子测量技术，2021, 44(19): 148-154. LI Peng, DING Qianwen. OSTU segmentation algorithm based on sparrow algorithm optimization[J]. Electronic Measurement Technology, 2021, 44(19): 148-154. Cited in this article [1]

[18]	戈一航，杨光永，徐天奇，等. 基于SSA优化PID在移动机器人路径跟踪中的研究[J]. 国外电子测量技术，2021, 40(09): 64-69. GE Yihang, YANG Guangyong, XU Tianqi, at al. Research on optimized PID based on SSA in path tracking of mobile robot[J]. Foreign Electronic Measurement Technology, 2021, 40(09): 64-69. Cited in this article [1]