Parallel solutions of large Riccati equations using epsilon decomposition

We present a new parallel algorithm which is designed to accurately solve large, sparse Riccati equations. The algorithm utilizes epsilon decompositions to obtain a good initial approximation for the solution, and subsequently combines the Arnoldi Krylov subspace method with Newton´s iterative process to refine this approximation. Experimental results are presented for three large electric power systems, illustrating that in a multiprocessor environment this approach can produce accurate solutions with only modest demands on the execution time and memory