基于正交变换与置信域的量测方差估计与权重设置算法

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (2227 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract In the practical applications of state estimation,it is difficult to obtain the measurement variances and set the weights of measurements.With the computation of state estimation getting harder,the convergence of the existing measurement variance estimation algorithm can not be guaranteed.To solve this problem,an algorithm based on orthogonal transformation and trust region to estimate measurement variance and set weight is proposed in this paper.The numerical stability of measurement variance estimation is improved by the orthogonal transformation method,which can reduce the condition number of the coefficient matrix at each iteration.According to the reduced results of orthogonal transformation,combining with Lagrange multipliers method,a new measurement variance estimation model is established.The trust region is considered as the constraint of the objective function to ensure that each estimation result data is in a confidence interval.The simulation results of the IEEE 14 bus system,IEEE 30 bus system and IEEE 118 bus system show the effectiveness of the proposed algorithm.

Key words： State estimation orthogonal transformation trust region measurement variance weight convergence

Received: 15 June 2015 Published: 21 November 2016

PACS:

TM734

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Lu Zhigang
	Tian Shasha
	Shao Qi
	Wu Jie

Cite this article:

Lu Zhigang,Tian Shasha,Shao Qi等. Measurement Variance Estimation and Weights Configuration Algorithm Based on Orthogonal Transformation and Trust Region[J]. Transactions of China Electrotechnical Society, 2016, 31(21): 67-74.

URL:

https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2016/V31/I21/67

[1] 顾锦汶.对有关标准中关于状态估计的一些不同意见[J].电力系统自动化,2014,38(2):134-135.
Gu Jinwen.Disagreements discussion on state estimation in related standards[J].Automation of Electric Power Systems,2014,38(2):134-135.
[2] Schweppe F C,Wildes J.Power system static-state estimation,part I:exact model[J].IEEE Transactions on Power Apparatus and Systems,1970,89(1):120-125.
[3] Robert E L,William F T.State estimation in power systems,part I:theory and feasibility[J].IEEE Transactions on Power Apparatus and Systems,1970,89(3):345-352.
[4] 于尔铿.电力系统状态估计[M].北京:水利电力出版社,1985:54-60.
[5] Abur A,Expósito A G.Power system state estimation,theory and implementation[M].New York:Marcel Dekker,2004:20-58.
[6] 李静,罗雅迪,赵昆,等.考虑大规模风电接入的快速抗差状态估计研究[J].电力系统保护与控制.2014,42(22):113-118.
Li Jing,Luo Yadi,Zhao Kun,et al.Research of fast and robust state estimation considering large-scale wind power intergration[J].Power System Protection and Control,2014,42(22):113-118.
[7] 李碧君,薛禹胜,顾锦汶,等.状态估计中选取量测权值的新原则[J].电力系统自动化,2000,24(8):10-14.
Li Bijun,Xue Yusheng,Gu Jinwen,et al.A new criterion of determining measurement weights in power system state estimation[J].Automation of Electric Power Systems,2000,24(8):10-14.
[8] Vanslyck L S,Allemong J J.Operating experience with the AEP state estimator[J].IEEE Transactions on Power Systems,1988,3(2):521-526.
[9] 黄知超,谢霞,王斌.结合模糊综合评判与决策的电力系统状态估计[J].电力系统保护与控制,2015,43(7):65-69.
Huang Zhichao,Xie Xia,Wang Bin.Power system state estimation combined with fuzzy comprehensive evaluation and decision-making[J].Power System Protection and Control,2015,43(7):65-69.
[10]刘广一,于尔铿,夏祖治.量测系统误差方差的估计与修正[J].中国电机工程学报,1990,10(6):31-39.
Liu Guangyi,Yu Erkeng,Xia Zuzhi.Estimation and update of measurement system error variance[J].Proceedings of the CSEE,1990,10(6):31-39.
[11]Liu Guangyi,Yu Erkeng,Song Y H.Noval algorithms to estimate and adaptively update measurement error variance using power system state estimation results[J].Electric Power Systems Research,1998,47:57-64.
[12]Shan Zhong,Ali A.Auto tuning of measurement weights in WLS state estimation[J].IEEE Transactions on Power System,2004,19(4):2006-2013.
[13]郑伟业,吴文传,张伯明,等.基于内点法的交直流混联系统抗差状态估计[J].电力系统保护与控制,2014,42(21):1-7.
Zheng Weiye,Wu Wenchuan,Zhang Boming,et al.Robust state estimatior for AC/DC hybrid power system based on an interior point method[J].Power System Protection and Control,2014,42(21):1-7.
[14]郭烨,张伯明,吴文传,等.直角坐标下含零注入约束的电力系统状态估计修正牛顿法[J].中国电机工程学报,2012,32(19):96-100.
Guo Ye,Zhang Boming,Wu Wenchuan,et al.Power system state estimation solution with zero injection constraints using modified Newton method[J].Proceedings of the CSEE,2012,32(19):96-100.
[15]郭烨,吴文传,张伯明,等.极坐标下含零注入约束的电力系统状态估计的修正牛顿法与快速解耦估计[J].中国电机工程学报,2012,32(22):113-117.
Guo Ye,Wu Wenchuan,Zhang Boming,et al.Power system state estimation solution with zero injection constraints using modified Newton method and fast decoupled method in polar coordinate[J].Proceedings of the CSEE,2012,32(22):113-117.
[16]Pandian A,Parthasarathy K,Soman S A.Towards faster givens rotations based power system state estimator[J].IEEE Transactions on Power Systems,1999,14(3):837-843.
[17]Pires R C,Costa A S,Mili L.Iteratively reweighted least-squares state estimation trough givens rotations[J].IEEE Transactions on Power Systems,1999,14(4):1499-1506.
[18]杜正春,牛振勇,方万良.基于分块QR分解的一种状态估计算法[J].中国电机工程学报,2003,23(8):51-55.
Du Zhengchun,Niu Zhenyong,Fang Wanliang.A block QR based power system state estimation algorithm[J].Proceedings of the CSEE,2003,23(8):51-55.
[19]郭瑞鹏,邵学俭,韩祯祥.基于分块吉文斯旋转的电力系统状态估计[J].中国电机工程学报,2006,26(12):26-31.
Guo Ruipeng,Shao Xuejian,Han Zhenxiang.A blocked Givens rotations based algorithm for power system state estimation[J].Proceedings of the CSEE,2006,26(12):26-31.
[20]Costa A S,Salgado R,Haas P.Globally convergent state estimation based on Givens rotations[J].IEEE Transactions on Power Systems,2014,29(5):2381-2390.
[21]Pajic S,Clements K A.Power system state estimation via globally convergent methods[J].IEEE Transactions on Power Systems,2005,20(4):1683-1689.
[22]Sousa A A,Torres G L,Caizares C A.Robust optimal power flow solution using trust region and interior-point methods[J].IEEE Transactions on Power Systems,2011,26(2):487-499.