[1]江辉,陈笠,帅士奇,等.基于无迹粒子滤波的电网动态谐波估计[J].深圳大学学报理工版,2016,33(1):80-88.[doi:10.3724/SP.J.1249.2016.01080]
 Jiang Hui,Chen Li,Shuai Shiqi,et al.Estimation of dynamic harmonics in power systems based on unscented particle filter[J].Journal of Shenzhen University Science and Engineering,2016,33(1):80-88.[doi:10.3724/SP.J.1249.2016.01080]
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基于无迹粒子滤波的电网动态谐波估计()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第33卷
期数:
2016年第1期
页码:
80-88
栏目:
电子与信息科学
出版日期:
2016-01-20

文章信息/Info

Title:
Estimation of dynamic harmonics in power systems based on unscented particle filter
文章编号:
20160111
作者:
江辉1陈笠1帅士奇1彭建春2
1)深圳大学光电工程学院,广东深圳 518060
2)深圳大学机电与控制工程学院,广东深圳 518060
Author(s):
Jiang Hui1 Chen Li1 Shuai Shiqi1 and Peng Jianchun2
1) College of Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China
2) College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China
关键词:
电力系统电能质量动态谐波估计粒子滤波 无迹卡尔曼滤波无迹粒子滤波
Keywords:
power system power quality dynamic harmonic estimation particle filter unscented Kalman filter unscented particle filter
分类号:
TM 711;TM 93
DOI:
10.3724/SP.J.1249.2016.01080
文献标志码:
A
摘要:
提出一种基于无迹粒子滤波(unscented particle filter, UPF)算法的电网动态谐波估计方法.通过无迹卡尔曼滤波算法得到电网动态谐波状态量的估计值和协方差,运用这些结果改进传统粒子滤波算法的重要密度函数,采用粒子滤波算法得到电网动态谐波的最优估计值.该方法克服了无迹卡尔曼滤波算法(unscented Kalman filter, UKF)对噪声要求为高斯分布的限制和传统粒子滤波(particle filter,PF)算法易退化的缺点,保留了UKF对非线性问题的较好处理和PF强抗干扰性能力.仿真结果表明,在高斯噪声和非高斯噪声情况下,UPF算法得到的电网动态谐波幅值、相位的估计值都更接近真实值.
Abstract:
This paper proposes a new method for estimating dynamic harmonics in power systems based on the unscented particle filter (UPF) algorithm. The UPF algorithm is used to estimate the values and covariance of the state variables of the dynamic harmonics in power systems. These estimated values are used to generate the importance density function of particle filter (PF) algorithm. The optimal estimation of dynamic harmonics in the power system is achieved by using the derived PF algorithm. The proposed method overcomes not only the restriction of Gaussian distribution noise required in unscented Kalman filters (UKF) but also the drawback of easy degeneration for conventional PF. In addition, it retains the high performance of UKF in processing nonlinearity and the strong anti-interference capability of PF.Experiments show that the estimates of dynamic harmonic amplitude and phase by the proposed method are closer to the true values under both Gaussian noise and non-Gaussian noise situations.

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相似文献/References:

[1]江辉,刘顺桂,尹远兴,等.基于小波和改进S变换的电能质量扰动分类[J].深圳大学学报理工版,2014,31(1):23.[doi:10.3724/SP.J.1249.2014.01023]
 Jiang Hui,Liu Shungui,Yin Yuanxing,et al.Classification of power quality disturbance based on wavelet and improved S-transform[J].Journal of Shenzhen University Science and Engineering,2014,31(1):23.[doi:10.3724/SP.J.1249.2014.01023]
[2]江辉,谢兴,王志忠,等.基于优化无迹Kalman滤波的电网动态谐波估计[J].深圳大学学报理工版,2015,32(2):188.[doi:10.3724/SP.J.1249.2015.02188]
 Jiang Hui,Xie Xing,Wang Zhizhong,et al.Dynamic harmonic estimation based on optimized unscented Kalman filter model[J].Journal of Shenzhen University Science and Engineering,2015,32(1):188.[doi:10.3724/SP.J.1249.2015.02188]

备注/Memo

备注/Memo:
Received:2015-11-05;Accepted:2015-12-30
Foundation:National Natural Science Foundation of China (51477104);Shenzhen Science and Technology Research Foundation for Basic Project (JCYJ20140418193546100)
Corresponding author:Professor Jiang Hui. E-mail: huijiang @szu.edu.cn
Citation:Jiang Hui, Chen Li, Shuai Shiqi, et al. Estimation of dynamic harmonics in power systems based on unscented particle filter [J]. Journal of Shenzhen University Science and Engineering, 2016, 33(1): 80-88.(in Chinese)
基金项目:国家自然科学基金资助项目(51477104);深圳市基础研究计划资助项目(JCYJ20140418193546100)
作者简介:江辉(1968—),女,深圳大学教授.研究方向:智能电网、电能质量分析与控制.E-mail:huijiang@szu.edu.cn
引文:江辉,陈笠,帅士奇,等.基于无迹粒子滤波的电网动态谐波估计[J]. 深圳大学学报理工版,2016,33(1):80-88.
更新日期/Last Update: 2016-01-14