Abstract-A common approach to distributed control design is to impose sparsity constraints on the controller structure. Such constraints, however, may greatly complicate the control design procedure. This paper puts forward an alternative structure, which is not sparse yet might nevertheless be well suited for distributed control purposes. The structure appears as the optimal solution to a class of coordination problems arising in multi-agent applications. The controller comprises a diagonal (decentralized) part, complemented by a rank-one coordination term. Although this term relies on information about all subsystems, its implementation only requires a simple averaging operation.

Abstract-We consider a scenario where a wind farm is given a power set point below its actual power production capacity. The objective is to dynamically redistribute power in order to minimize the fatigue loads experienced by the turbines, while maintaining the desired power production at all times. We show that this can be done in a distributed way by coordinating neighboring turbines. The result is a control scheme where both the synthesis and the resulting control law only require each turbine to communicate with a limited set of neighboring turbines.

We consider a wind power plant of megawatt wind turbines operating in derated mode. When operating in this mode, the wind power plant controller is free to distribute power set-points to the individual turbines, as long as the total power demand is met. In this work, we design a controller that exploits this freedom to reduce the fatigue on the turbines in the wind power plant. We show that the controller can be designed in a decentralized manner, such that each wind turbine is equipped with a local low-complexity controller relying only on few measurements and little communication. As a basis for the controller design, a linear wind turbine model is constructed and verified in an operational wind power plant of megawatt turbines. Due to limitations of the wind power plant available for tests, it is not possible to implement the developed controller; instead the final distributed controller is evaluated via simulations using an industrial wind turbine model. The simulations consistently show fatigue reductions in the magnitude of 15-20 %.

Turbines operating in wind farms are coupled by the wind flow. This coupling results in limited power production and increased fatigue loads on turbines operating in the wake of other turbines. To operate wind farms cost effectively, it is important to understand and address these effects. In this paper, we derive a stationary model for turbine interaction. The model has a simple intuitive structure, and the parameters have a clear interpretation. Moreover, the effect of upwind turbines on a downwind turbine can be completely determined through information from its closest neighbor. This makes the model well-suited for distributed control. In an example, we increase total power production in a farm, by coordinating the individual power production of the turbines. The example points to an interesting model property: decreasing power in an upwind turbine causes downwind turbines to pose less of an obstacle for the wind, provided that they maintain their level of power capture.

Abstract-We investigate the potential of using previewed wind speed measurements for damping wind turbine fore-aft tower oscillations. Using recent results on continuous-time H 2 preview control, we develop a numerically efficient framework for the feedforward controller synthesis. One of the major benefits of the proposed framework is that it allows us to account for measurement distortion. This results in a controller that is tailored to the quality of the previewed data. A simple yet meaningful parametric model of the measurement distortion is proposed and used to analyze the effects of distortion characteristics on the achievable performance and on the required length of preview. We demonstrate the importance of accounting for the distortion in the controller synthesis and quantify the potential benefits of using previewed information by means of simulations based on real-world turbine data. I. INTRODUCTIONAn evident trend in the area of wind energy during the past decades is a continuous growth of wind turbine dimensions. Modern day commercial turbines typically stand more than 90 m tall, with a blade span of over 120 m [1]. As a consequence of such a large size, structural loads experienced by turbines becomes a central issue. These loads shorten the life span of the turbine and increase its maintenance costs. Alternatively, turbines with a higher tolerance to structural loads require a more rigid structure and, as a result, higher construction costs. For this reason, load reduction is an important factor in decreasing the cost of wind energy.In this paper, we focus on exploiting wind speed preview for reducing tower fore-aft oscillations in wind turbines with collective pitch control. The idea of using preview in the control of wind turbines was discussed in [1], [2] and has been a subject of interest for many researchers in the last few years. The use of preview in cyclic pitch control was considered in [3]. Model predictive control with preview was studied in a collective pitch setting in [4], [5] and in an individual pitch setting in [6]. The benefit of model predictive techniques is in their ability to account for hard input, output and state constraints, which is particularly useful when operating near rated conditions. These methods, however, may require heavy online computations and impede the analysis of the problem. The use of preview in individual pitch control was considered in [7] using the LMI approach to H ∞ optimization. In [8], [9], preview control for load reduction was studied using model inversion methods and adaptive control algorithms based on recursive least squares.