基于改进S变换-TT变换的电压暂降特性研究
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摘要
针对S变换的窗函数固定,以及在检测扰动信号的起止时刻、幅值变化、相位变化时的检测精度不高的问题,在S变换中引入两个调谐因子,得到一种改进的S变换,并对改进的S变换进行傅里叶反变换得到TT变换,将改进的S变换与TT变换相结合应用到主要引起电压暂降的3种暂降源中,并在MATLAB软件上对这3种暂降扰动源信号进行了仿真分析。仿真结果表明,所提的方法比使用S变换方法在检测电压暂降信号上具有更高的检测精度和更好的效果,为更好地提取暂降特征信息以及暂降源的识别打下基础。
In view of the fixed window function of S-transformation and the problem of detection accuracy when detecting the start and end moments of disturbance signal, amplitude variation, and phase change, this paper introduces two tuning factors in S-transformation to obtain an improved one. S transform, and the inverse transform of the improved S transform to get the TT transform, the improved S transform and the TT transform are applied to the three sources of the disturbance that mainly cause the voltage sag, and on the MATLAB to the three a kind of temporary disturbance source signal was detected and analyzed. The MATLAB simulation results show that the proposed method has better effect and higher detection precision than the S-transform method in detecting voltage sags, which lays the foundation for better extraction of the characteristics of sags and identification of temporary sources.
In view of the fixed window function of S-transformation and the problem of detection accuracy when detecting the start and end moments of disturbance signal, amplitude variation, and phase change, this paper introduces two tuning factors in S-transformation to obtain an improved one. S transform, and the inverse transform of the improved S transform to get the TT transform, the improved S transform and the TT transform are applied to the three sources of the disturbance that mainly cause the voltage sag, and on the MATLAB to the three a kind of temporary disturbance source signal was detected and analyzed. The MATLAB simulation results show that the proposed method has better effect and higher detection precision than the S-transform method in detecting voltage sags, which lays the foundation for better extraction of the characteristics of sags and identification of temporary sources.
引文
[1] 苗竹梅, 王冲.刘伟,等. 电子企业的电压暂降分析与对策[J]. 智能电网, 2016,4(12):1171-1174.
[2] 刘旭娜, 肖先勇, 汪颖. 电压暂降严重程度及其测度、不确定性评估方法[J]. 中国电机工程学报, 2014, 34(4):644-658.
[3] 吴丽娜. 电压暂降检测分析及抑制措施研究[D]. 保定: 华北电力大学,2015.
[4] 张淑清,李盼,师荣艳,等. 基于改进S变换的电能质量扰动分类新方法[J].仪器仪表学报,2015, 36(4):927-934.
[5] 梅娟, 黄纯, 戴栩生,等. 采用TT变换的电能质量扰动检测与分类方法[J]. 电力系统及其自动化学报, 2016, 28(3):24-29.
[6] 肖先勇,崔灿,汪洋, 等. 电压暂降分类特征可比性、相关性及马氏距离分类法[J]. 中国电机工程学报, 2015, 35(6):1299-1305.
[7] 刘超, 黎涛,王华. 静止无功补偿器接入的配网短路故障特征及保护整定策略[J]. 电力系统及其自动化学报, 2017, 29(6):113-117.
[8] 孙丛丛,王致杰,陈丽娟,等. 基于MATLAB的电力系统故障仿真与检测方法研究[J]. 电力学报, 2016,31(1):1-7,62.
[9] 李夏林,刘雅娟,朱武. 基于配电网的复合电压暂降源分类与识别新方法[J]. 电力系统保护与控制,2017, 45(2):131-139.
[10] 黄南天,袁翀,张卫辉,等. 采用最优多分辨率快速S变换的电能质量分析[J]. 仪器仪表学报, 2015, 36(10):2174-2183.
[11] 金智,尹柏强. 基于广义S变换的高斯领域时频滤波方法[J]. 电子测量与仪器学报,2015, 29(1):124-131.
[12] 杨万清,姜学朴,刘冰. 基于广义S变换和PSO-ELM的电能质量扰动信号识别[J].电力电容器与无功补偿, 2017,38(2):129-134,140.
[13] WANG Q, ZHANG Y S, LIU H W, et al. A novel interference detection method of STAP based on simplified TT transform [J]. Mathematical Problems in Engineering, 2017(2):1-9.
[14] 康兵,康逸群,钟鑫. TT变换及其对角线在暂态电能质量现象识别中的应用[J].陕西电力,2015, 43(12):43-47,56.
[15] JASHFAR S, ESMAEILI S, ZAREIANJAHROMI M. Classification of power quality disturbances using S-transformand TT-transform based on the artificial neural network[J]. Turkish Journal of Electrical Engineering & Computer Sciences, 2014, 21(6):1528-1538.
[2] 刘旭娜, 肖先勇, 汪颖. 电压暂降严重程度及其测度、不确定性评估方法[J]. 中国电机工程学报, 2014, 34(4):644-658.
[3] 吴丽娜. 电压暂降检测分析及抑制措施研究[D]. 保定: 华北电力大学,2015.
[4] 张淑清,李盼,师荣艳,等. 基于改进S变换的电能质量扰动分类新方法[J].仪器仪表学报,2015, 36(4):927-934.
[5] 梅娟, 黄纯, 戴栩生,等. 采用TT变换的电能质量扰动检测与分类方法[J]. 电力系统及其自动化学报, 2016, 28(3):24-29.
[6] 肖先勇,崔灿,汪洋, 等. 电压暂降分类特征可比性、相关性及马氏距离分类法[J]. 中国电机工程学报, 2015, 35(6):1299-1305.
[7] 刘超, 黎涛,王华. 静止无功补偿器接入的配网短路故障特征及保护整定策略[J]. 电力系统及其自动化学报, 2017, 29(6):113-117.
[8] 孙丛丛,王致杰,陈丽娟,等. 基于MATLAB的电力系统故障仿真与检测方法研究[J]. 电力学报, 2016,31(1):1-7,62.
[9] 李夏林,刘雅娟,朱武. 基于配电网的复合电压暂降源分类与识别新方法[J]. 电力系统保护与控制,2017, 45(2):131-139.
[10] 黄南天,袁翀,张卫辉,等. 采用最优多分辨率快速S变换的电能质量分析[J]. 仪器仪表学报, 2015, 36(10):2174-2183.
[11] 金智,尹柏强. 基于广义S变换的高斯领域时频滤波方法[J]. 电子测量与仪器学报,2015, 29(1):124-131.
[12] 杨万清,姜学朴,刘冰. 基于广义S变换和PSO-ELM的电能质量扰动信号识别[J].电力电容器与无功补偿, 2017,38(2):129-134,140.
[13] WANG Q, ZHANG Y S, LIU H W, et al. A novel interference detection method of STAP based on simplified TT transform [J]. Mathematical Problems in Engineering, 2017(2):1-9.
[14] 康兵,康逸群,钟鑫. TT变换及其对角线在暂态电能质量现象识别中的应用[J].陕西电力,2015, 43(12):43-47,56.
[15] JASHFAR S, ESMAEILI S, ZAREIANJAHROMI M. Classification of power quality disturbances using S-transformand TT-transform based on the artificial neural network[J]. Turkish Journal of Electrical Engineering & Computer Sciences, 2014, 21(6):1528-1538.