Methodology for multiarea state estimation solved by a decomposition method

•The state estimation is addressed by a decentralized scheme with minimum information exchange.•The proposed methodology is the decomposition method called optimality condition decomposition.•The proposed strategy converges faster due to it does not require the multipliers’ updating.

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.