Abstract
This paper deals with the control problems of a wind turbine working in its nominal zone. In this region, the wind turbine speed is controlled by means of the pitch angle, which keeps the nominal power constant against wind fluctuations. The non-uniform profile of the wind causes tower displacements that must be reduced to improve the wind turbine lifetime. In this work, an adaptive control structure operating on the pitch angle variable is proposed for a nonlinear model of a wind turbine provided by FAST software. The proposed control structure is composed of a gain scheduling proportional–integral (PI) controller, an adaptive feedforward compensation for the wind speed, and an adaptive gain compensation for the tower damping. The tuning of the controller parameters is formulated as a Pareto optimization problem that minimizes the tower fore-aft displacements and the deviation of the generator speed using multi-objective genetic algorithms. Three multi-criteria decision making (MCDM) methods are compared, and a satisfactory solution is selected. The optimal solutions for power generation and for tower fore-aft displacement reduction are also obtained. The performance of these three proposed solutions is evaluated for a set of wind pattern conditions and compared with that achieved by a classical baseline PI controller.
Highlights
Wind energy has a leading role in the current great demand for renewable energy and is one of the sources that has experienced a greater growth in recent decades [1]
The results show a significant improvement of 92.9%, 93.3, and 89.5 in the IAEωg index; 41%, 37.3%, and 43% in the CVRxt index; 41.1%, 29.4%, and 45.9 in the CVRMfa index; and 3.6%, 2.7%, and 4.5% in the CVRMss index of the satisfactory solutions, optimal IAEωg, and optimal CVRxt with respect to the baseline controller (BSC)
The proposed control strategy is based on the following control loops: the first loop to maintain the generator speed at its nominal value reducing the fluctuations and keeping the generated power constant through a gain scheduling PI controller with adaptive feedforward control, and the second loop to reduce the tower fore-aft displacements through an active tower damping control (ATDC)
Summary
Wind energy has a leading role in the current great demand for renewable energy and is one of the sources that has experienced a greater growth in recent decades [1]. Some commercial controllers use pitch control to actively mitigate the tower fore-aft (f-a) movement when the wind turbine is operating at region IV This is called Active Tower Damping Control (ATDC) and is usually performed adding another control loop to the basic turbine speed controller [17]. In [31], an intelligent optimization method has been proposed to optimize the potential performance though yaw control strategy of a real wind turbine manufactured by China Ming Yang Wind Power (CMYWP) In this case, the Pareto front had two conflicting objectives: the minimization of the power reduction factor and the minimization of the yaw actuator.
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