Back to Search Start Over

Distributed State Estimation of Multi-region Power System based on Consensus Theory

Authors :
Shiwei Xia
Qian Zhang
Jiangping Jing
Zhaohao Ding
Jing Yu
Bing Chen
Haiwei Wu
Source :
Energies, Vol 12, Iss 5, p 900 (2019)
Publication Year :
2019
Publisher :
MDPI AG, 2019.

Abstract

Effective state estimation is critical to the security operation of power systems. With the rapid expansion of interconnected power grids, there are limitations of conventional centralized state estimation methods in terms of heavy and unbalanced communication and computation burdens for the control center. To address these limitations, this paper presents a multi-area state estimation model and afterwards proposes a consensus theory based distributed state estimation solution method. Firstly, considering the nonlinearity of state estimation, the original power system is divided into several non-overlapped subsystems. Correspondingly, the Lagrange multiplier method is adopted to decouple the state estimation equations into a multi-area state estimation model. Secondly, a fully distributed state estimation method based on the consensus algorithm is designed to solve the proposed model. The solution method does not need a centralized coordination system operator, but only requires a simple communication network for exchanging the limited data of boundary state variables and consensus variables among adjacent regions, thus it is quite flexible in terms of communication and computation for state estimation. In the end, the proposed method is tested by the IEEE 14-bus system and the IEEE 118-bus system, and the simulation results verify that the proposed multi-area state estimation model and the distributed solution method are effective for the state estimation of multi-area interconnected power systems.

Details

Language :
English
ISSN :
19961073
Volume :
12
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Energies
Publication Type :
Academic Journal
Accession number :
edsdoj.426cdf0b6401433386eb161e7d224aec
Document Type :
article
Full Text :
https://doi.org/10.3390/en12050900