Model Predictive Control for Power Optimization in a Hydrostatic Wind Turbine

Abstract Model predictive control (MPC) is applied to a mid-sized hydrostatic (HST) wind turbine for maximizing power capture in this paper. This study focuses on the torque control in region 2, which tracks the desired rotor speed so that the turbine can operate at the optimum tip-speed ratio (TSR) for maximum power. Preliminary study shows that the widely used control law has a good control performance in steady-state wind conditions. However due to wind turbulence, the turbine operates at tip-speed ratios far away from the optimal point. This deviation is not only due to the large rotor inertia, but also due to the characteristics of the control. An MPC controller is proposed to track the desired rotor speed by using the future prediction of wind speed. To consider the potential advantage, the MPC controller is applied to a 50 kW HST wind turbine. A wind speed step change is selected as a basic test of transient response. The control performance of the MPC is evaluated and compared with the control law. Results show that the MPC controller in a smaller wind speed step change shows a faster response than control law, but a large overshoot is observed. In a larger wind speed change, the MPC controller loses control when the wind speed steps down. This indicates the MPC controller in this study has limited effective operation range since it uses a linearized plant model and the wind turbine is a highly nonlinear system. Future work includes the optimization of MPC controller parameters to reduce the overshoot during the wind speed change and the design of multiple MPC controllers for wide operation range

Optimal control of wind turbines for distributed power generation

textWind energy represents one of the major renewable energy sources that can meet future energy demands to sustain our lifestyle. During the last few decades, the installation of wind turbines for power generation has grown rapidly worldwide. Besides utility scale wind farms, distributed wind energy systems contributes to the rise in wind energy penetration. However, the expansion of distributed wind energy systems is faced by major challenges such as the system’s reliability in addition to the environmental impacts. This work is intended to explore various control algorithms to enable the distributed wind energy systems to face the aforementioned challenges. First of all, a stall regulated fixed speed wind turbine augmented with a variable ratio gearbox has been proven to enhance the wind energy capture at a relatively low cost, and considered as an attractive design for small wind energy systems. However, the high reliability advantage of traditional fixed-speed wind turbines can be affected by the integration of the variable ratio gearbox. A portion of this work is intended to develop a control algorithm that extends the variable ratio gearbox service life, thus improves overall system reliability and reduces the expected operational cost. Secondly, a pitch regulated variable speed wind turbines dominates the wind energy industry as it represents a balance between cost and flexibility of operation. They can be used for midsized wind power generation. Optimizing its wind energy capture while maintain high system reliability has been the one of the main focuses of many researchers. Another portion of this work introduces a model predictive control framework that enhances the reliability of pitch regulated variable speed wind turbines, thus improves their operational cost. Finally, one of the major environmental challenges facing the continuous growth of wind energy industry is the noise emitted from wind turbines. The severity of the noise emission problem is more significant for small and medium sized wind turbines installed in the vicinity of residential areas for distributed power generation. Consequently, the last portion of this work is intended to investigate the potential of wind turbine control design to reduce noise emission in different operating conditions with minimal impact on power generationMechanical Engineerin