Efficient computation of Riccati-based optimal control for power system models

The computational technique for solving continuous algebraic Riccati equations governed from a very large dimensional power system with sophisticated ingredients requires highly expensive time dealings and invade by the infeasible rate of convergence. The aim of the work is mainly focused on acquiring the optimal control for the large-scale power system model and stabilizing the corresponding system through the Riccati based feedback stabilization. To achieve the desired goal, a nested iterative Kleinman-Newton (K-N) method is proposed by means of Alternative Direction Implicit (ADI) technique. The proposed algorithm will allow the structure-preserving simulations and can be efficiently applied to the perturbed systems with proper adaptation.