Power system dynamic model reduction by means of an iterative SVD-Krylov model reduction method

摘要

This paper introduces the application of an iterative SVD-Krylov algorithm for dynamic model reduction of power systems. The method is a two-sided projection combining advantages of the singular value decomposition based and the Krylov-based model reduction methods. The significance and accuracy of the method are numerically investigated. The full linearized dynamic model of the original nonlinear power system is determined and used as the input of dynamic reduction technique. The capability of this technique in keeping dominant oscillation modes after reduction is utilized as the comparison criteria. Physical relationship between the reduced and the original system is also discussed by mean of coherency in power systems.