Verification and simulation analysis of wind turbine control based on linear parameter varying gain scheduling

Abstract: With the installed capacity of wind turbines increasing, the wind turbine output characteristics and optimal operation obtain much more concerns in the industry. This paper discusses the influence of wind turbulence on the performance of wind turbines. Wind turbine is a complex nonlinear system. Due to structure load coupling, wind variation and pitch actions, the parameters of aerodynamic subsystem are changing with operation state. Usually, PI (proportional integral) control algorithm is satisfied for a linear time invariant system. To obtain better performance, a nonlinear system needs an advanced control algorithm. To address this issue, we propose a linear parameter varying (LPV) gain scheduling control to mitigate the influence of wind turbulence on wind turbine performance. At different wind speed with variable pitch and rotor speed, the LPV control can adjust feedback gain to satisfy the changing operation point. First, we introduce the stability of LPV system and LPV controller design process. Once the stability conditions are reached, the closed-loop system is stable. Then, we derive a control model with a 2 MW wind turbine based on an actual double-fed induction generator. The input is a recommended turbulence model, Kaimal. In order to check the simulation model, the field data are compared with simulation results. The generator power and torque have similar statistic characteristics. So the model is suitable for simulation and the simulation results are credible. According to the analysis of field data, wind turbulence has a great impact on wind turbine performance, such as fatigue damage of gearbox and decreasing power generation efficiency. Therefore the economic benefits are reduced in the entire lifetime of wind turbine. Simulation results of LPV control algorithm and PI control algorithm are obtained by the software Bladed under 12 and 16 m/s wind turbulence, respectively. In time domain, the generator speed and torque are varying due to the wind turbulence. The amplitude of fluctuations under PI controller is bigger than that under LPV controller. However, the differences are not significant. To illustrate the characteristics of wind turbulence affecting wind turbine performance, the simulation results are also analyzed in frequency domain. Through spectrograms, it is observed that the peaks are concentrated on multiple rotational frequencies. The primary components are multiple 3P frequencies. Therefore, decreasing the components of multiple 3P frequencies can mitigate load fluctuation. At rated wind speed, the tower shadow effect is dominant in the load fluctuations of wind turbine. However, at high wind speed, the fluctuation does not occurs only on multiple rotational frequencies, so the turbulence has bigger influence on wind turbine performance compared with the situation at rated wind speed. In the simulation, the wind speed is 16 m/s and the turbulence intensity is 0.16; compared with PI controller, the fluctuations of gearbox's low speed shaft torque and power are reduced by 41.8% and 35.1% respectively on 3P frequency by LPV controller. Less load fluctuation on shaft torque leads to less fatigue damage on gearbox. Also smooth power output is friendly to the grid. Therefore, the proposed control algorithm can alleviate the influence of wind turbulence and enhance the performance of wind turbine, which can bring lower wind energy cost and longer wind turbine lifetime.