Abstract-As wind energy becomes a larger portion of the world's energy portfolio and wind turbines become larger and more expensive, wind turbine control systems play an ever more prominent role in the design and deployment of wind turbines. The goals of traditional wind turbine control systems are maximizing energy production while protecting the wind turbine components. As more wind generation is installed there is an increasing interest in wind turbines actively controlling their power output in order to meet power setpoints and to participate in frequency regulation for the utility grid. This capability will be beneficial for grid operators, as it seems possible that wind turbines can be more effective at providing some of these services than traditional power plants. Furthermore, establishing an ancillary market for such regulation can be beneficial for wind plant owner/operators and manufacturers that provide such services. In this tutorial paper we provide an overview of basic wind turbine control systems and highlight recent industry trends and research in wind turbine control systems for grid integration and frequency stability.
Combined feedback/feedforward blade pitch control is compared to industry standard feedback control when simulated in realistic turbulent winds. The feedforward controllers are designed to reduce fatigue loads, increasing turbine lifetime and therefore reducing the cost of energy. Various collective pitch and individual pitch versions of two feedforward designs are studied: Gain-Scheduled Model-Inverse and Gain-Scheduled Shaped Compensator. The input to the feedforward controller is a measurement of incoming wind speed, which could potentially be provided by LIDAR. Three of the designs reduce structural loading compared to standard feedback control, without reducing power production.
Combined feedback/feedforward blade pitch control is compared to industry standard feedback control when simulated in realistic turbulent winds. The feedforward controllers are designed to reduce fatigue loads, increasing turbine lifetime and therefore reducing the cost of energy. Three feedforward designs are studied: Non-Causal Series Expansion, Preview Control, and Optimized FIR Filter. The input to the feedforward controller is a measurement of incoming wind speed, which could potentially be provided by lidar. Noncausal series expansion and Preview Control methods reduce blade root loads but increase tower bending in simulation results. The optimized FIR filter reduces loads overall, keeps pitch rates low, and maintains rotor speed regulation and power capture, while using imperfect wind measurements provided by a lidar model.
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