Robust MPC Tower Damping for Variable Speed Wind Turbines

Evans, Martin; Cannon, Mark; Kouvaritakis, B.

doi:10.1109/tcst.2014.2310513

Cited by 71 publications

(40 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…PID control [252,253], LQG [254], sliding mode control [255], and nonlinear state feedback [256]. A single controller capable of operating the wind turbine over the entire wind regime may also be designed using control based on gain scheduling of a linear parameter varying system [257,258] and MPC [259,260]. The inherent turbine inertia may lead to difficulty in tracking the optimal power point in turbulent wind conditions.…”

Section: Windmentioning

confidence: 99%

“…based on a hill climbing algorithm, to empirically track the maximum power point on-line [262]. Uncertainty in future wind conditions has been accounted for in MPC-based approaches using robust optimization [260] and by on-line identification of the wind time series via machine learning [263]. Authors have developed similar methods to control other types of wind turbines, e.g.…”

Section: Windmentioning

confidence: 99%

See 1 more Smart Citation

Sustainability and process control: A survey and perspective

Daoutidis

Zachar

Jogwar

2016

Journal of Process Control

View full text Add to dashboard Cite

Section: Windmentioning

confidence: 99%

Section: Windmentioning

confidence: 99%

Sustainability and process control: A survey and perspective

Daoutidis

Zachar

Jogwar

2016

Journal of Process Control

View full text Add to dashboard Cite

“…In addition, individual pitch control (IPC) and tower damping control can be used to specifically attenuate unsteady loads that play no part in power generation. The IPC provides additional pitch demand signals to each blade in order to balance the loads across the rotor plane, typically in response to measurements of the flap-wise blade root bending moments [2]- [4], whilst tower damping control provides a further adjustment to the collective blade pitch angle in order to reduce excessive tower vibrations, in response to tower foreaft velocity measurements [5]- [8]. Typically, and for reasons of simplicity of implementation favoured by the industry, IPCs and tower damping controllers are designed separately from the CPC, and carefully in order to avoid cross-excitation [9]- [12].…”

Section: Introductionmentioning

confidence: 99%

Estimation and Control of Wind Turbine Tower Vibrations Based on Individual Blade-Pitch Strategies

Lio

Jones

Rossiter

2019

IEEE Trans. Contr. Syst. Technol.

View full text Add to dashboard Cite

Abstract-In this paper, we present a method to estimate the tower fore-aft velocity based upon measurements from blade load sensors. In addition, a tower dampening control strategy is proposed, based upon an individual blade pitch control architecture that employs this estimate. The observer design presented in this paper exploits the Coleman transformations that convert a time-varying turbine model into one that is linear and time-invariant, greatly simplifying the observability analysis and subsequent observer design. The proposed individual pitch-based tower controller is decoupled from the rotor speed regulation loop and hence does not interfere with the nominal turbine power regulation. Closed-loop results, obtained from high fidelity turbine simulations, show close agreement between the tower estimates and the actual tower velocity. Furthermore, the individual-pitchbased tower controller achieves similar performance compared to the collective-pitch-based approach but with negligible impact upon the nominal turbine power output.Index Terms-State estimation of dynamical systems, Kalman filter, active damping control, wind energy.

show abstract

“…Model predictive control (MPC) is widely adopted in engineering for multi-objective problems with linear or nonlinear constraints. It has been employed in WECS for generator control [10,11], power converter control [12,13], wind-battery hybrid control [14] and other multi-objective control [15]. Mechanical load and conversion efficiency are considered in [16,17].…”

Section: Introductionmentioning

confidence: 99%

A Flexible Maximum Power Point Tracking Control Strategy Considering Both Conversion Efficiency and Power Fluctuation for Large-inertia Wind Turbines

et al. 2017

View full text Add to dashboard Cite

Abstract:In wind turbine control, maximum power point tracking (MPPT) control is the main control mode for partial-load regimes. Efficiency potentiation of energy conversion and power smoothing are both two important control objectives in partial-load regime. However, on the one hand, low power fluctuation signifies inefficiency of energy conversion. On the other hand, enhancing efficiency may increase output power fluctuation as well. Thus the two objectives are contradictory and difficult to balance. This paper proposes a flexible MPPT control framework to improve the performance of both conversion efficiency and power smoothing, by adaptively compensating the torque reference value. The compensation was determined by a proposed model predictive control (MPC) method with dynamic weights in the cost function, which improved control performance. The computational burden of the MPC solver was reduced by transforming the cost function representation. Theoretical analysis proved the good stability and robustness. Simulation results showed that the proposed method not only kept efficiency at a high level, but also reduced power fluctuations as much as possible. Therefore, the proposed method could improve wind farm profits and power grid reliability.

show abstract

Robust MPC Tower Damping for Variable Speed Wind Turbines

Cited by 71 publications

References 19 publications

Sustainability and process control: A survey and perspective

Sustainability and process control: A survey and perspective

Estimation and Control of Wind Turbine Tower Vibrations Based on Individual Blade-Pitch Strategies

A Flexible Maximum Power Point Tracking Control Strategy Considering Both Conversion Efficiency and Power Fluctuation for Large-inertia Wind Turbines

Contact Info

Product

Resources

About