基于奇异值分解的同调机群识别方法

doi:10.19595/j.cnki.1000-6753.tces.161893

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (1458 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract This paper presented a novel approach to identify coherent generators using singular value decomposition (SVD) in power systems. The key information reflecting coherency was extracted by SVD directly from the real-time power angle values provided by wide-area measurement system (WAMS). From the point of energy, the weight matrix with low dimensions was constructed by referring to several main singular values, the number of which was adaptively determined by energy contribution rate defined in the paper. Coherent generators were identified by applying cluster analysis on the weight matrix. The proposed method is simple, and entails small amount of calculation, so that it is suitable for complex interconnected power grid especially. Meanwhile, this paper discussed the on-line application of the method. The results show that it has high computational speed and potential to be applied online. Furthermore, the results of coherency identification can be expressed by graphs, which is beneficial to control and analysis of power systems. The effectiveness and correctness of the proposed method was validated by simulation results on IEEE39-bus system and China southern power grid (CSG).

Key words： Power system coherency identification singular value decomposition clustering analysis

Received: 01 December 2016 Published: 26 February 2018

PACS:

TM76

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Zhu Qiaomu
	Chen Jinfu
	Duan Xianzhong
	You Hao
	Li Benyu

Cite this article:

Zhu Qiaomu,Chen Jinfu,Duan Xianzhong等. A Coherent Generators Identification Method Based on Singular Value Decomposition[J]. Transactions of China Electrotechnical Society, 2018, 33(3): 591-600.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.161893 OR https://dgjsxb.ces-transaction.com/EN/Y2018/V33/I3/591

[1] 薛禹胜. 运动稳定性量化理论——非自治非线性多刚体系统的稳定性分析[M]. 南京: 江苏科学技术出版社, 1999.
[2] Tao Jiang, Jia Hongjie, Yuan Haoyu.Projection pursuit: a general methodology of wide-area coherency detection in bulk power grid[J]. IEEE Transactions on Power Systems, 2016, 31(4): 2776-2786.
[3] 丁磊, 郭一忱, 陈青, 等. 电力系统主动解列的可行解列时窗研究[J]. 电工技术学报, 2015, 30(12): 415-421.
Ding Lei, Guo Yichen, Chen Qing, et al.Research on feasible splitting time interval of controlled islanding[J]. Transactions of China Electrotechnical Society, 2015, 30(12): 415-421.
[4] 徐劭翔, 苗世洪, 李超, 等. 基于改进递归融合算法的电力系统主动解列断面搜索方法[J]. 电工技术学报, 2016, 31(15): 117-124.
Xu Shaoxiang, Miao Shihong, Li Chao, et al.A research method for power system controlled islanding surface based on improved recursive merge algorithm[J]. Transactions of China Electrotechnical Society, 2016, 31(15): 117-124.
[5] 赵晋泉, 邓晖, 吴小辰, 等. 基于广域响应的电力系统暂态稳定控制技术评述[J]. 电力系统保护与控制, 2016, 44(5): 1-9.
Zhao Jinquan, Deng Hui, Wu Xiaochen, et al.Review on power system transient stability control technologies based on PMU/WAMS[J]. Power System Protection and Control, 2016, 44(5): 1-9.
[6] 唐飞, 贾骏, 刘涤尘, 等. 一种考虑发电机同调分群的大电网快速主动解列策略[J]. 电工技术学报, 2016, 31(17): 32-40.
Tang Fei, Jia Jun, Liu Dichen, et al.A fast active islanding scheme considering generators’ coherent partition[J]. Transactions of China Electrotechnical Society, 2016, 31(17): 32-40.
[7] 胥威汀, 戴松灵, 张全明, 等. 区域互联电网故障解列方法综述[J]. 中国电机工程学报, 2015, 35(11): 2756-2769.
Xu Weiting, Dai Songling, Zhang Quanming, et al.Commnets and overviews on the islanding methods of large interconnected power grid[J]. Proceedings of the CSEE, 2015, 35(11): 2756-2769.
[8] Rou H, Vittal V, Wang X.Slow coherency-based islanding[J]. IEEE Transactions on Power Systems, 2004, 19(1): 483-491.
[9] 倪敬敏, 沈沉, 谭伟, 等. 一种基于非平衡点处线性化的同调识别方法[J]. 电力系统自动化, 2010, 34(20): 7-12.
Ni Jingmin, Shen Chen, Tan Wei, et al.A coherence identifying method based on non-equilibrium point[J]. Automation of Electric Power Systems, 2010, 34(20): 7-12.
[10] 潘炜, 刘文颖, 杨以涵. 采用受扰轨迹和独立分量分析技术识别同调机群的方法[J]. 中国电机工程学报, 2008, 28(25): 86-92.
Pan Wei, Liu Wenying, Yang Yihan.Method of identifying coherent generator groups by independent component analysis through perturbed trajectories[J]. Proceedings of the CSEE, 2008, 28(25): 86-92.
[11] 安军, 穆钢, 徐炜彬. 基于主成分分析法的电力系统同调识别[J]. 电网技术, 2009, 33(3): 25-28.
An Jun, Mu Gang, Xu Weibin.Method of identifying coherent generators groups by independent component analysis through perturbed trajectories[J]. Power System Technology, 2009, 33(3): 25-28.
[12] Avdaković S, Bećirović E, Nuhanović A, et al.Generator coherency using the wavelet phase difference approach[J]. IEEE Transactions on Power Systems, 2014, 29(1): 271-278.
[13] Vahidnia A, Ledwich G, Palmer E, et al.Generator coherency and area detection in large power systems[J]. IET Generation, Transmission & Distribution, 2012, 6(9): 874-883.
[14] Phillips R D, Watson L T, Wynne R H, et al.Feature reduction using a singular value decomposition for the iterative guided spectral class rejection hybrid classifier[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2009, 64(1): 107-116.
[15] Julio S, Tatiana A, Bikash P.Data compression in smart distribution systems via singular value decomposition[J] . IEEE Transactions on Smart Grid, 2017, 8(1): 275-284.
[16] 刘献栋, 杨绍普, 申永军, 等. 基于奇异值分解的突变信息检测新方法及其应用[J]. 机械工程学报, 2002, 38(6): 102-105.
Liu Xiandong, Yang Shaopu, Shen Yongjun, et al.New method of detecting abrupt information based on singular value decomposition and its application[J]. Journal of Mechanical Engineering, 2002, 38(6): 102-105.
[17] 何田, 刘献栋, 李其汉. 噪声背景下检测突变信息的奇异值分解技术[J]. 振动工程学报, 2006, 19(3): 399-403.
He Tian, Liu Xiandong, Li Qihan.An improved method of detecting abrupt information based on singularity value decomposition in noise background[J]. Journal of Vibration Engineering, 2006, 19(3): 399-403.
[18] 何峰, 黄庆明, 高文. 一种基于奇异值分解的图像匹配算法[J]. 计算机研究与发展, 2010, 47(1): 23-32.
He Feng, Huang Qingming, Gao Wen.An image matching algorithm based on singular value decomposition[J]. Journal of Computer Research and Development, 2010, 47(1): 23-32.
[19] 刘涵, 梁莉莉, 黄令帅. 基于分块奇异值分解的两级图像去噪算法[J]. 自动化学报, 2015, 41(2): 439-444.
Liu Han, Liang Lili, Huang Lingshuai.Two-stage image denoising using patch-based singular value decomposition[J]. Acta Automatica Sinica, 2015, 41(2): 439-444.
[20] Lehtolaa L, Karsikasb M, Koskinena M, et al.Effects of noise and filtering on SVD-based morphological parameters of the T wave in the ECG[J]. Journal of Medical Engineering & Technology, 2008, 32(5): 400-407.
[21] 齐子元, 米东, 徐章遂. 奇异谱分析在机械设备故障诊断中的应用[J]. 噪声与振动控制, 2008, 28(1): 82-85.
Qi Ziyuan, Mi Dong, Xu Zhangsui.Application of singular spectral analysis in mechanical device fault diagnosis[J]. Noise and Vibration Control, 2008, 28(1): 82-85.
[22] 包兴先, 李昌良, 刘志慧. 基于低秩Hankel矩阵逼近的模态参数识别方法[J]. 振动与冲击, 2014, 33(20): 57-62.
Bao Xingxian, Li Changliang, Liu Zhihui.Model parameters identification based on low rank approximation of Hankel matrix[J]. Journal of Vibration and Shock, 2014, 33(20): 57-62.
[23] 杨明, 刘先忠. 矩阵论[M]. 2版. 武汉: 华中科技大学出版社, 2005.
[24] Zhang Rui, Xu Yan, Dong Zhaoyang, et al.Post-disturbance transient stability assessment of power systems by a self-adaptive intelligent system[J]. IET Generation Transmission & Distribution, 2015, 9(3): 296-305.
[25] Horn R A, Johnson C R.Topics in matrix analysis[M]. New York: Cambridge University Press, 1991.
[26] 冯康恒, 张艳霞, 刘志雄, 等. 基于广域信息的同调机群在线识别方法[J]. 电网技术, 2014, 38(8): 2082-2086.
Feng Kangheng, Zhang Yanxia, Liu Zhixiong, et al.A wide area information based online recognition of coherent generators in power system[J]. Power System Technology, 2014, 38(8): 2082-2086.
[27] Anand R, Jeffrey D U.Mining of massive datasets[M]. Cambridge: Cambridge University Press, 2011.
[28] Peña J M, Lozano J A, Larrañaga P.An empirical comparison of four initialization methods for k-means algorithm[J]. Pattern Recognition Letters, 1999, 20(10): 1027-1040.
[29] Pai A M.Energy function analysis for power system stability[M]. Boston: Kluwer Academic Publishers, 1989: 256.