A multi-objective optimal nonlinear control of variable speed wind turbine

Abstract

Control design for variable speed wind turbine system is one of most challenge to engineer today. Wind energy conversion system that includes complex combination of aero dynamics and electrical phenomena together with anonymous action of wind speed making control system sophisticated. Beside the nonlinearity model of wind turbine, the basic control strategy for wind turbine is maximizing the power captured by tracking closely the optimal point of Tip-Speed-Ratio. However, tower dynamics and mechanical loads may cause fatigue damage on several devices, thereby reducing the useful life of the system and decreasing quality of the power connected to the grid. Different working regimes of wind turbine in term of wind speed, fast variations of wind and the limitations of mechanical electrical system are also a tackle when designing controller. In this paper, we present advanced control algorithm Nonlinear Model Predictive Control (NMPC) which is promising control theory interested by many researchers resent years. All mixed criterions optimization problems are generally handled by integrated cost function. The optimality of the system based on the trade-off energy conversion and control input minimization that reduces mechanical stress of the drive train. The simulation will show the validation of theory idea of NMPC is an efficient way to handle multi-objectives synthesis over the famous Linear Quadratic Gaussian (LQG) in stall regulated variable speed wind turbine control.