Intelligent optimal control of wind power generating system by a complemented linear quadratic gaussian approach

Abstract

As wind turbines continue to grow in size and flexibility and are deployed in more hostile environments, the need to develop advanced control schemes will be essential to deliver the lowest possible energy costs. A sophisticated control strategy is presented to compensate for the complicated effects of a stochastic operating environment and nonlinearities inherent in wind turbine generator (WTG) dynamics that cause parametric uncertainties. In low to medium winds the objective is to follow wind speed variations with the target of optimizing aerodynamic efficiency. At above-rated wind speeds, the controller's purpose is to add damping to the drive train while the pitch control mechanism ensures the maximum power constraint is respected, thereby preventing rotor overspeed. Simulations based on modeling the wind speed as a stochastic process, and the WTG as a multimass model with a soft shaft linking the turbine with the asynchronous generator, show the efficacy of the proposed paradigm in meeting the control objectives.