Wind Farm Load Reduction via Parametric Programming Based Controller Design

Spudić, Vedrana; Baotić, Mato; Perić, Nedjeljko

doi:10.3182/20110828-6-it-1002.02956

Cited by 16 publications

(24 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The conceptually most straightforward architecture is centralized control in which all sensors and actuators are connected to one central controller. Consequently, this approach is also used by many authors . The disadvantages of this approach are the massive amount of communication from hundreds of turbines to one controller and the problems that occur if this one controller fails.…”

Section: Minimize Fatigue Loading For the Wind Turbines In The Farmmentioning

confidence: 96%

“…Methods such as model predictive control (MPC) and linear quadratic control (LQG) have been used in, e.g. some research . From an optimization point of view, the advantage of these methods is that they amount to convex optimizations, which do not have problems with local minima, and they produce guaranteed stable controllers.…”

Section: Minimize Fatigue Loading For the Wind Turbines In The Farmmentioning

confidence: 99%

See 1 more Smart Citation

Survey of wind farm control—power and fatigue optimization

2014

View full text Add to dashboard Cite

The main goal of this paper is to establish the present state of the art for wind farm control. The control area that will be focused on is the mechanical/aerodynamic part, which includes the wind turbines, their power production, fatigue and wakes affecting neighbouring wind turbines. The sub‐objectives in this area of research are as follows: (i) maximizing the total wind farm power production; (ii) following a reference for the total wind farm active power; and (iii) doing this in a manner that minimizes fatigue loading for the wind turbines in the farm. Each of these sub‐objectives is discussed, including the following important control issues: choice of input and output, control method and modelling used for controller design and simulation. The available literature from industry is also considered. Finally, a conclusion is presented discussing the established results, open challenges and necessary research. Copyright © 2014 John Wiley & Sons, Ltd.

show abstract

Section: Minimize Fatigue Loading For the Wind Turbines In The Farmmentioning

confidence: 96%

Section: Minimize Fatigue Loading For the Wind Turbines In The Farmmentioning

confidence: 99%

Survey of wind farm control—power and fatigue optimization

2014

View full text Add to dashboard Cite

show abstract

“…Steinbuch et al proposed a centralized farm‐level controller to maximize the power production of wind farms. Since this time, various other centralized control systems have been proposed . A downside to centralized controllers is the large amount of rapid communication necessary between the controller and individual wind turbines.…”

Section: Introductionmentioning

confidence: 99%

The effect of timescales on wind farm power variability with nonlinear model predictive control

Saunders

Marshall

Hines³

2017

Wind Energy

View full text Add to dashboard Cite

Model predictive control techniques enable operators to balance multiple objectives in large wind farms, but the controller design depends on modeling effects that propagate at different timescales. This paper uses nonlinear model predictive control to investigate how wind farm power variability can be reduced both by varying ratios of three timescales impacting the system control and by inclusion of a power variability minimization measure in the controller objective function. Tests were conducted to assess how different timescale ratios affect the average farm power and power variability. Power variability measures are shown to be sensitive to the ratio of the incident wind period and the turbine time delay, particularly for cases with dominant incident wind frequencies. The average farm power increases in a series of steps as the controller time horizon increases, which corresponds to time horizon values required for wakes disturbances to propagate to downstream turbines. A second set of tests was conducted in which various measures of power variability were incorporated into the controller objective function and shown to yield significant reductions in farm power variability without significant reductions in farm power output. The controller was found to utilize two different approaches for achieving power variability reduction depending on the formulation of the controller objective function. These results have important implications for the design and operation of wind power plants, including the importance of considering the frequency components of wind during turbine siting and the potential to reduce power variability through the use of farm‐level coordinated control. Copyright © 2017 John Wiley & Sons, Ltd.

show abstract

“…This beckons a scheme of coordination of individual wind turbine actions to increase the overall efficiency of the plant and reduce fatigue and loads on wind turbines [10]. With an increased responsibility in power generation, wind farms have other tasks to perform such as regulation and stabilization of power plants and may not be required to run at a full capacity at all times [9]. Many researchers have tackled cooperative wind farm control problems.…”

Section: Introductionmentioning

confidence: 99%

“…The approach of maximizing the power of an individual turbine renders suboptimal in terms of wind farm power production due to coupled aerodynamic effects and mechanical loadings [9]. This beckons a scheme of coordination of individual wind turbine actions to increase the overall efficiency of the plant and reduce fatigue and loads on wind turbines [10].…”

Section: Introductionmentioning

confidence: 99%

Optimal Power Planning of Wind Turbines in a Wind Farm

Vishwakarma¹,

Xu²,

Lin³

2017

EPES

View full text Add to dashboard Cite

Abstract:Wind energy is attractive in the presence of climate concerns and has the potential to dramatically reduce the dependency on nonrenewable energy resources. With the increase in wind farms there is a need to improve the efficiency in power allocation and power generation among wind turbines. In this paper, a hierarchical algorithm including a cooperative level and an individual level is developed for power coordination and planning in a wind farm. In the cooperative level, a constrained quadratic programming problem is formulated and solved to allocate the power to wind turbines considering the aerodynamic effects of wake interaction and the power generation capabilities of wind turbines. In the individual level, a method based on the local pursuit strategy is studied to connect the cooperative level power allocation and the individual level power generation using a virtual leader-follower scheme. The stability of individual wind turbine power generation is analyzed. Simulations are used to show the advantages of the method.

show abstract

Wind Farm Load Reduction via Parametric Programming Based Controller Design

Cited by 16 publications

References 2 publications

Survey of wind farm control—power and fatigue optimization

Survey of wind farm control—power and fatigue optimization

The effect of timescales on wind farm power variability with nonlinear model predictive control

Optimal Power Planning of Wind Turbines in a Wind Farm

Contact Info

Product

Resources

About