Active Power Control Of Wind Farm Research Articles

A non-centralized predictive control strategy for wind farm active power control: A wake-based partitioning approach

Owing to wake effects, the power production of each turbine in a wind farm is highly coupled to the operating conditions of the other turbines. Wind farm control strategies must take into account these couplings and produce individual power commands for each turbine. In this case, centralized control approaches might be prone to failures due to the high computational burden and communication dependency. To overcome this problem, this paper proposes a non-centralized scheme based on splitting the wind farm into almost uncoupled sets of turbines by solving a mixed-integer partitioning problem. In each set of turbines, a model predictive control strategy seeks to optimize the distribution of the power set-points among turbines such that the impact of the power losses due to the wake effect is reduced. Then, a supervisory controller coordinates the generation of each group to satisfy the power demanded by the grid operator. The effectiveness of the proposed control scheme in terms of reduction of computational costs and power regulation is confirmed by simulations for a wind farm of 42 turbines.

Large-eddy simulation study of wind farm active power control with a coordinated load distribution

In this paper, an active power control (APC) approach for wind farms is studied, for a case in which the wind turbines interact with each other aerodynamically through their wakes. We demonstrate that the structural loadings on the individual wind turbines can be coordinated to expand their lifetimes, while the wind farm production tracks a power reference signal. We propose an additional feedback control loop in order to adjust the distribution of the regulated power demands among the wind turbines, exploiting the non-unique solutions of APC for wind farms. The axial induction factor of each wind turbine is considered as a control input to influence the overall wind farm performance. The applicability of the controller is tested with a wind farm example consisting of 2×3 turbines with partial wake overlaps and detailed interactions with the atmospheric boundary layer, simulated with the PArallelized Large-eddy simulation Model (PALM). The results demonstrate the effectiveness of the proposed approach and point to some future studies that may improve and extend the performance.

Sliding mode control-based active power control for wind farm with variable speed wind generation system

Active power control in wind farm, implemented with hierarchical structure (including the central wind farm active power control system and the control system of variable speed wind generation system), has significantly improved the wind-farm-generated power. However, the interaction between the control system of variable speed wind generation system and the central wind farm active power control system has not been considered in the control system design of both sides. The wind generation system with active power control in wind farm, as a high-order nonlinear large-scale system, will not only autonomous operating with maximum power capture, but also being demanded to regulate power output according to the power set points ordered by the central wind farm active power control system. Therefore, robust active power control of wind farm is clearly necessary. In this article, sliding mode is used to design the active power control system for wind farm, which makes the output power of wind farm track the active power order from the power grid operator asymptotically. Particularly, the control system of the variable speed wind generation system is designed with cascaded structure: the input of the internal rotational speed control loop of the wind generation system is controlled by the external power loop which tracks the specified power set point. Then, based on the dynamic model of wind farm, the central wind farm active power control system is designed to control the total output power of wind farm by using the sliding mode control method. Furthermore, in order to ensure the given power set point is within the regulation capability of the wind generation system, the proportional distribution strategy is utilized to specify the power set point according to the available output power of each wind generation system, which is quantified by ultra-short term power prediction model. The proposed approach is illustrated by implementing it to the active power control of a wind-farm model in simulation. The simulation results demonstrate that the proposed method outperforms the method based on proportional-integral control.