An intelligent controller for a remote wind-diesel power system - design and dynamic performance analysis

This paper presents an intelligent controller based on a neural network for a wind-diesel power system equipped with a stall regulated wind turbine run an induction generator. The goal for the wind-diesel power system is to design an intelligent controller to maintain a good power quality under varying wind and load conditions. On the other hand, the controller has to show acceptable closed-loop performance including stability, robustness, optimal energy, steady state, and transient performance at a permissible level of control effort. Moreover, such a controller has to be highly adaptive to various operating conditions and independent of model parameters that can be uncertain. This paper presents an inverse dynamic neural controller, which consists of an inverse dynamic neural model and generalized minimum variance control. This proposed controller is applied to design an integrated nonlinear controller to provide control input from excitation system and governor system at the same time.