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Markov Chains for Multipartitioning Power System State Estimation Networks

Habiballah, I.O. and Ghosh-Roy, R. and Irving, M.R. (1998) Markov Chains for Multipartitioning Power System State Estimation Networks. Electric Power System Research, 45 (2). pp. 135-140.

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Abstract

This paper presents a new and efficient algorithm for multipartitioning an observable power system state estimation network into observable subnetworks. The partitioning algorithm, which uses the spanning tree of an observable network, is based on Markov chains and has a stochastic basis, rather than a heuristic derivation. This algorithm is faster and provides all the possible optimal partitions of a spanning tree. Once the spanning tree is optimally partitioned into full rank subspanning trees, the interconnected lines between the partitioned subnetworks can be obtained directly from the original network. Computational examples using large power networks are given, to illustrate the properties of the proposed algorithm.



Item Type:Article
Date:May 1998
Date Type:Publication
Subjects:Electrical
Divisions:College Of Engineering Sciences > Electrical Engineering Dept
Creators:Habiballah, I.O. and Ghosh-Roy, R. and Irving, M.R.
Email:ibrahimh@kfupm.edu.sa, UNSPECIFIED, UNSPECIFIED
ID Code:347
Deposited By:Dr SHARIF IQBAL SHEIKH
Deposited On:15 Mar 2008 16:58
Last Modified:12 Apr 2011 13:06

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