Nonlinear state space modeling of a variable speed wind power generation system

Abstract

New problems emerging from the increased production of power from renewable resources are becoming a good challenge. To face the new challenges, accurate modeling of such systems is required. For example, to be able to apply advanced control strategies, usually a linearized state space representation of the system is needed. Taking a variable speed cage machine wind generation system as the case study, in this paper a nonlinear state space model is developed first and then linearized. As the wind speed changes randomly, the parameters of the equivalent linear model also change to track these changes. Results of simulation studies show that the linearized model matches well with the original nonlinear state space model. The nonlinear and linear state space models derived in this paper can be used in the development of advanced control strategies.