基于统计方法的电网谐波状态估计误差分析

Abstract
Figure/Table
References
Related Citation (7)

Download: PDF (690 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Harmonic state estimation (HSE) is the basis of harmonic elimination, and its precision is largely dependent on the measurement errors, harmonic network parameters and the algorithm. The IEEE 14-bus harmonic testing system was used as an example and the error analysis of the estimation result was conducted by use of the statistical approach such as probability density functions and cumulative probability density functions. When measurement errors and parameter errors obey gauss distribution or uniform distribution, the errors of HSE were investigated and the corresponding effect of uncertainty errors was analyzed. The total least squares(TLS) for HSE was adopted and the algorithm had considered both the parameter and measurement errors. The results indicate that the estimated values are obeying gauss distribution approximately when the topological structure of harmonic network is fixed, and the higher harmonic order is, the narrower of fiducial interval will be. The parameter errors for the HSE cannot be neglected, and the TLS has better inhibition about the gauss distribution error.

Key words： Harmonic state estimation total least squares measurement errors parameter error error analysis

Received: 25 February 2008 Published: 14 February 2014

PACS:

TM711

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Zhou Niancheng
	Tan Guihua
	He Jiansen
	Zhao Yuan
	Yang Fang

Cite this article:

Zhou Niancheng,Tan Guihua,He Jiansen等. Error Analysis in Harmonic State Estimation of Power System Based on the Statistical Approach[J]. Transactions of China Electrotechnical Society, 2009, 24(6): 109-114.

URL:

http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2009/V24/I6/109

[1] 王兆安, 杨君, 刘进军. 谐波抑制和无功功率补偿[M]. 北京: 机械工业出版社, 1998.
[2] 程浩忠, 艾芊, 张志刚, 等. 电能质量[M]. 北京：清华大学出版社, 2006.
[3] Heydt G T. Identification of harmonic sources by a state estimation technique[J]. IEEE Transactions on Power Delivery, 1989, 4(1): 569-576.
[4] Meliopoulos A P S, Zhang F, Zelingher S. Power system harmonic state estimation[J]. IEEE Transactions on Power Delivery, 1994, 9(3): 1701- 1709.
[5] Du Z P, Arrillaga J, Watson N. Continuous harmonic state estimation of power systems[J]. IEE Proceedings-Generation, Transmission and Distribution, 1996, 143(4): 329-336.
[6] Du Z P, Arrillaga J, Watson N, et al. Identification of harmonic sources of power systems using state estimation[J]. IEE Proceedings-Generation, Trans- mission and Distribution, 1999, 146(1): 7-12.
[7] 吴笃贵, 徐政. 基于相量量测的电力系统谐波状态估计(I)——理论、模型与求解算法[J]. 电工技术学报, 2004, 19(2): 64-68.
[8] Liao Huaiwei. Power system harmonic state estimation via sparsity maximization[C]. Proc. of IEEE/PES General Meeting, Montreal, 2006.
[9] Kent K C Yu, Neville R Watson. Error analysis in static harmonic state estimation: a statistical approach[J]. IEEE Transactions on Power Delivery, 2005, 20(2): 1045-1050.
[10] Liao Huaiwei. Power system harmonic state estimation and observability analysis via sparsity maximization[J]. IEEE Transactions on Power Systems, 2007, 20 (1): 15-23.
[11] 孙宏斌, 高峰, 张伯明, 等. 电力系统最小信息损失状态估计的信息学原理[J]. 中国电机工程学报, 2005, 25(6): 11-16.
[12] Cichocki Andrzej, Amari Shun-ichi. 自适应盲信号与图像处理[M]. 吴正国, 唐劲松, 张林柯, 等译. 北京: 电子工业出版社, 2005.
[13] 傅崇伦. 测量误差的概率分布[J]. 成都电讯工程学院学报, 1981, 3(3): 56-65.
[14] 胡广书. 数字信号处理[M]. 北京: 清华大学出版社, 2004.