This study focuses on the development of optimal torque (OT) control, which is a commonly used method for maximum power point tracking (MPPT). Due to the sluggish response of wind turbines with high inertia, conventional OT control was improved to increase MPPT efficiency by dynamically modifying the generator torque versus rotor speed curve. An idea that tracking a local interval of wind speed where the wind energy is primarily distributed rather than the total range of wind speed variation is applied in this study. On this basis, an effective tracking range (ETR) that corresponds to the local interval of wind speed with concentrated wind energy distribution is proposed and an improved OT control based on ETR is developed. In this method, based on a direct relationship between ETR and wind conditions, the torque curve can be quickly optimised so that higher and more stable MPPT efficiency can be achieved under varying wind conditions. Meanwhile, MPPT efficiency enhancement by reducing tracking range without increasing torque discrepancy leads to a low cost of generator torque fluctuation and drive train load. Finally, simulations based on fatigue, aerodynamics, structures, and turbulence (FAST) code and experiments conducted on a wind turbine simulator are presented to verify the proposed method.

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Wind turbine simulator (WTS) is an important test rig for validating the control strategies of wind turbines (WT). Since the inertia of WTSs is much smaller than that of WTs, the inertia compensation scheme is usually employed in WTSs for replicating the slow mechanical behavior of WTs. In this paper, it is found that the instability of WTSs applying the inertia compensation scheme, characterized by the oscillation of compensation torque, is caused by the one-step time delay produced in the acceleration observation. Hence, a linear discrete model of WTS considering the time delay of acceleration observation is developed and its stability is analyzed. Moreover, in order to stably simulate WTs with large inertia, an improved inertia compensation scheme, applying a first-order digital filter to mitigate deviation response induced by the time delay, is proposed. And, the criterion for selecting the filter coefficients is established based on the stability condition analysis. Finally, the WTS with the proposed scheme is validated by simulations and experiments.

Wind turbine simulators (WTSs), devised for pre-validation of control strategies for wind energy conversion system, commonly employ the inertia compensation scheme for reproducing mechanical behaviours similar to real wind turbines (WTs). However, it is found in this study that when a WT with large inertia is simulated, the time delay in command communication from control unit to motor driver, usually neglected in the existing inertia compensation scheme, results in the oscillating acceleration response and consequently leads to instability of the WTS system. As a result, the existing WTS is unable to stably simulate large-inertia WTs, which significantly limits its applicability. Hence, in this study, a linear discrete model of the inertia compensation part that considers time delay of acceleration observation and communication is developed. On the basis of this model, an improved inertia compensation scheme in which a high-order filter is introduced to eliminate the deviation of acceleration response caused by the two types of time delay is proposed. Finally, the improved inertia compensation scheme and its applicability to simulating a 600 kW WT developed by National Renewable Energy Laboratory are experimentally verified.

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In the research of singular signal detection, the selection of wavelet function is the first issue to be considered. How to choose the wavelet function for singular signal detection is emphasized in this paper. It's based on the fact that the wavelet function can be perfectly selected by comprehensive considering the characteristics of wavelet function, such as compact support, regularity and vanishing moments. The simulation is presented to illustrate the validity and feasibility of the method.