Nonlinear Dynamic Power System Model Reduction Analysis Using Balanced Empirical Gramian

Abstract

This paper presents an empirical Gramian balanced reduction method which efficiently solves nonlinear power system model reduction problems. This method projects the nonlinear power system dynamic model to a lower dimension subspace and the reduced model can retain the original nonlinear system input and output dynamic behaviors. A four-generator nonlinear power system, combining different factors which form empirical controllable and observable Gramian matrices, is used to analyze how external excitations and outputs affect balanced empirical Gramian reduction. The case verifies the feasibility and effectiveness of balanced empirical Gramian reduction method.