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Riccati-based feedback stabilization for unstable power system models

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Document pages: 30 pages

Abstract: In this article, the objective is mainly focused on the stabilization of theunstable power system models using the optimal feedback matrix achieved by theRiccati-based feedback stabilization approach. We aim to find the solution ofthe Continuous-time Algebraic Riccati Equations (CAREs) governed from theunstable power system models, which are of large-scale sparse index-1descriptor systems. We propose the projection-based Rational Krylov SubspaceMethod (RKSM) for the computation of the solution of the CAREs. The noveltiesof RKSM are sparsity-preserving computations and the implementation oftime-convenient adaptive shift parameters. We modify the Low-RankCholesky-Factor integrated Alternating Direction Implicit (LRCF-ADI) techniquebased nested iterative Kleinman-Newton (KN) method to a sparse form and adjustthis to solve the CAREs governed from unstable power system models. We comparethe results achieved by the Kleinman-Newton method with that of using the RKSM.The applicability and adaptability of the proposed methods are justifiedthrough the Brazilian Inter-Connected Power System (BIPS) models and theirtransient behaviors are comparatively analyzed by both tabular and graphicalapproaches.

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