Dynamic Model Reduction: An Overview of Available Techniques with Application to Power Systems

Abstract

This paper summarises the model reduction techniques used for the reduction of large-scale linear and nonlinear dynamic models, described by the differential and algebraic equations that are commonly used in control theory. The groups of methods discussed in this paper for reduction of the linear dynamic model are based on singular perturbation analysis, modal analysis, singular value decomposition, moment matching and methods based on a combination of singular value decomposition and moment matching. Among the nonlinear dynamic model reduction methods, proper orthogonal decomposition, the trajectory piecewise linear method, balancing-based methods, reduction by optimising system matrices and projection from a linearised model, are described. Part of the paper is devoted to the techniques commonly used for reduction (equivalencing) of large-scale power systems, which are based on coherency, synchrony, singular perturbation analysis, modal analysis and identification. Two (most interesting) of the described techniques are applied to the reduction of the commonly used New England 10-generator, 39-bus test power system.