PDF《基于线性约束最小均方的谐波检测算法》

第47卷第11期 电力系统保护与控制 Vol.

47 No.11 2019年6月1日Power System Protection and Control June 1,

2019 DOI: 10.19783/j.cnki.pspc.180863 基于线性约束最小均方的谐波检测算法 李裕杰

1 ,赵庆生

1 ,王旭平

1 ,郭尊2(1.太原理工大学电力系统运行与控制山西省重点实验室,山西 太原 030024;

2.华北电力大学电气与电子工程学院,北京 102206) 摘要: 最小均方(Least Mean Square, LMS)算法因其计算复杂度低、 稳定性好的特点已广泛应用于谐波检测领域中. 但为了避免权重偏移,进一步提高收敛速度,提出了一种基于线性约束最小均方(Linearly Constrained Least Mean Square, LCLMS)的谐波检测算法.该算法在 LMS 算法的基础上,对权重变量加入了一个线性约束条件,并应用于 不同高斯白噪声环境下谐波、间谐波信号的幅值和相角参数评估.最后又在稳态信号、动态信号和电弧炉算例下 检验了该算法的可行性.实验结果表明,该算法可以快速准确地检测不同环境下谐波的相关信息,且相比 LMS 算法有较快的收敛速度和较高的抗干扰能力. 关键词:最小均方;

谐波检测;

权重偏移;

线性约束最小均方;

线性约束 A harmonic detection algorithm based on linearly constrained least mean square LI Yujie1 , ZHAO Qingsheng1 , WANG Xuping1 , GUO Zun2 (1. Shanxi Key Laboratory of Power System Operation and Control, Taiyuan University of Technology, Taiyuan 030024, China;

2. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China) Abstract: In order to avoid weight offset and improve the convergence speed, this paper presents the harmonic detection algorithm based on linearly constrained least mean square, although the least mean square algorithm has been widely used in the field of harmonic detection because of its low computational complexity and good stability. New algorithm adds a linear constraint condition of the weight variable. The amplitude and phase of a power signal containing harmonics and inter-harmonics are estimated using this algorithm in the presence of white Gaussian noise under simulating environment. Finally, the algorithm is tested under the steady-state signal, the dynamic signal and the arc furnace model. According to experimental results, this algorithm can detect the information of harmonics quickly and accurately in different environments, and it has faster convergence speed and higher anti-interference ability compared with the LMS algorithm. This work is supported by National Natural Science Foundation for Young Scholars (No. 51505317) and Natural Science Foundation of Shanxi Province (No. 201601D102039). Key words: least mean square;

harmonic detection;

weight offset;

linearly constrained least mean square;

linear constraint

0 引言 由于电力系统中非线性负荷和电力电子器件的 增多,使得电网中电压电流的理想正弦波形遭到破 坏,从而降低了用户侧的用电质量,其中又以谐波 污染[1-2] 问题为主. 为了有效治理谐波污染,相继提出了一系列谐 基金项目:国家自然科学基金青年基金项目资助(51505317);

山西省自然科学基金项目资助(201601D102039) 波检测算法.目前主要有:快速傅里叶变换法[3-5] 、 神经网络法[6-7] 、瞬时无功功率法[8] 、小波变换法[9-10] 等.这些方法在一定程度上促进了谐波检测技术的 进步,但它们共有的检测系统开环的缺点使其在实 际应用中受到了限制. 由于自适应滤波[11-12] 方法是闭环系统,可根据 电网变化自动改变滤波器参数,具有自适应学习能 力,且对单相和三相系统均适应,因此该方法得到 了众多研究者的关注.美国斯坦福大学的 Widrow 和Hoff 提出的定步长 LMS(Least Mean Square)法[13] 李裕杰,等 基于线性约束最小均方的谐波检测算法 -