GPU-based power flow analysis with Chebyshev preconditioner and conjugate gradient method

Traditionally, linear equations in power system applications are solved by direct methods based on LU decomposition. With the development of advanced power system controls, the industrial and research community is more interested in simulating larger, interconnected power grids. Iterative methods such as the conjugate gradient method have been applied to power system applications in the literature for its parallelism potential with larger systems. Preconditioner, used for preconditioning the linear system for a better convergence rate in iterative computations, is an indispensable part of iterative solving process. This work implemented a polynomial preconditioner Chebyshev preconditioner with graphic processing unit (GPU), and integrated a GPU-based conjugate gradient solver. Results show that GPU-based Chebyshev preconditioner can reach around 46x speedup for the largest test system, and conjugate gradient can gain more than 4x speedup. This demonstrates great potentials for CPU application in power system simulation. (C) 2014 Published by Elsevier B.V.