| 引用本文: | 江辉,邹崇杰,谢兴,等.基于集合Kalman滤波的暂态电压扰动检测[J].电力系统保护与控制,2014,42(14):38-44.[点击复制] |
| JIANG Hui,ZOU Chong-jie,XIE Xing,et al.Transient voltage disturbances detection based on Ensemble-Kalman filtering[J].Power System Protection and Control,2014,42(14):38-44[点击复制] |
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| 摘要: |
| 随着电力系统中非线性负荷的增加，由暂态电压扰动引起的电能质量问题越来越严重，对暂态电压扰动信号的检测成为改善电能质量的关键。基于集合Kalman滤波方法进行暂态电压扰动检测分析，结合暂态电压扰动特点，构造了集合Kalman滤波的背景集合。由k-1，k-2时刻的电压状态修正值组成背景集合，然后进行递归运算，提取出实时的电压幅值，从而定位暂态扰动发生的起止时刻以及跟踪突变的幅值。仿真结果表明，所提方法能快速检测到电压暂降/突升、暂态电压脉冲信号发生的起止时刻，跟踪到突变幅值。其对谐波加电压暂降混合扰动信号的扰 |
| 关键词: 电能质量 暂态电压扰动 集合Kalman滤波 背景集合 扰动起止时刻 |
| DOI：10.7667/j.issn.1674-3415.2014.14.007 |
| 投稿时间：2013-10-16修订日期：2013-12-03 |
| 基金项目:国家自然科学基金资助项目(51177102); 深圳市基础研究计划项目(JCYJ20120613113140920、JCYJ20120817164050203) |
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| Transient voltage disturbances detection based on Ensemble-Kalman filtering |
| JIANG Hui,ZOU Chong-jie,XIE Xing,PENG Jian-chun |
| (College of Optoelectronic Engineering, Shenzhen University, Shenzhen 518061, China;College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518061, China) |
| Abstract: |
| With the increase of nonlinear loads in power system, power quality problems caused by transient voltage disturbance is more and more serious, the detection of transient voltage disturbance signal becomes the key to improve power quality. This paper proposes a transient voltage disturbance detection method based on Ensemble-Kalman filtering, the elements of Ensemble-Kalman filtering’s background ensemble are reformed according to the characteristics of transient voltage disturbance. The modified values of voltage state at k – 1 and k - 2 form the background ensemble, then the real-time voltage’s amplitude is obtained by recursive computation, thus the beginning and ending times of transient disturbances are positioned and abrupt amplitude is traced out. Simulation results show that the proposed method can quickly detect voltage’s sag/swell, precisely position the beginning and ending times of transient voltage disturbance, and track down the abrupt amplitude. The proposed method is more effective than the traditional Kalman filter (KF) and root-mean-square (RMS) algorithm. |
| Key words: power quality transient voltage disturbance Ensemble-Kalman filtering background ensemble beginning and ending times of disturbance |
