Methodology for multiarea state estimation solved by a decomposition method

被引:13
作者
Gonzalez, Xiomara [1 ]
Ramirez, Juan M. [1 ]
Marmolejo, J. A. [2 ]
Caicedo, Gladys [3 ]
机构
[1] CINVESTAV, IPN, Unidad Guadalajara, Guadalajara, Jalisco, Mexico
[2] Univ Anahuac, Huixquilucan, Mexico
[3] Univ Valle, Cali, Colombia
关键词
Decomposition methods; Lagrangian relaxation; Multiarea state estimation; Non-linear optimization; Optimization by decomposition; Decentralized architecture; PREDICTIVE CONTROL; DISPATCH; OPTIMIZATION; COORDINATION; ALGORITHM;
D O I
10.1016/j.epsr.2015.02.002
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
As power systems are large interconnected systems with a high degree of complexity, the control and operation of such systems become a challenging task. Thus, large-scale power systems are mostly operated as interconnected subsystems. In this paper, the state estimation problem is addressed through a decentralized optimization scheme with minimum information exchange among subsystems. This paper focuses on a methodology for solving the multiarea state estimation problem by a decomposition method. This method is derived from the Lagrangian relaxation method and is named optimality condition decomposition (OCD). Results are presented for the IEEE 118-buses test power system, which has been split into two and three subsystems. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:92 / 99
页数:8
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