Distributed State Estimation of Hybrid AC/HVDC Grids by Network Decomposition

State estimation (SE) for bulk power systems is traditionally formulated and executed as one integrated problem in a control center energy management system. This simultaneous approach may present challenges when the concerned network consists of different types of systems operated by different entities (independent system operator, transmission system operator, or utility). A leading example is provided by hybrid ac/high voltage dc (HVDC) grids. We propose a distributed solution method where the system network is decomposed into several subsystems on which SE problems are executed separately and are iteratively coordinated through updated boundary information. Hybrid ac/HVDC grids naturally decompose into ac and HVDC subsystems. The proposed method uses a Lagrangian relaxation-based approach and block-wise Gauss-Seidel solution technique to arrive at a solution. The paper describes the method in the context of HVDC grids based on voltage source converter (VSC) technology. It presents a unified modeling framework for monopole/bipole converter configurations, parallel converters, converter-less dc buses, and wind farm connections. Illustrations and test cases are drawn using hybrid ac/HVDC grids formed by IEEE 39 and 300 bus ac grid networks along with monopole and bipole VSC HVDC grids.