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Methodology for multiarea state estimation solved by a decomposition method
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DOI：10.1016/j.epsr.2015.02.002.png)
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Abstract
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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.
Keywords:
Decomposition methods
Lagrangian relaxation
Multiarea state estimation
Non-linear optimization
Optimization by decomposition
Decentralized architecture
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