Assessment of Extremum Seeking Control for Wind Farm Energy Production

2012 ◽  
Vol 36 (6) ◽  
pp. 701-715 ◽  
Author(s):  
Kathryn E. Johnson ◽  
Geraldine Fritsch
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Extremum Seeking ◽  
Extremum Seeking Control ◽  
Energy Capture ◽  
Time Varying Delay ◽  
Aerodynamic Interaction ◽  
Control Research ◽  
High Turbulence ◽  
Wind Input

Aerodynamic interaction among turbines grouped together in wind farms causes a decrease in the total energy extracted from the wind when compared to an equal number of widely dispersed turbines operating under the same wind input conditions as the wind farm. Extremum seeking control (ESC) is one strategy that holds promise for reducing this impact under certain wind input conditions. In this paper, we evaluate the effectiveness of ESC under different turbulence conditions, describing methods for addressing the complexities caused by the turbulent wind input and time-varying delay of the wind between turbines, where these two elements are the most important contributions compared to other wind farm control research. The results show that energy capture can be increased in low turbulence intensity conditions, but perhaps not in high turbulence conditions.

Real-Time Optimization of Wind Farm Energy Capture With Delay Compensated Nested-Loop Extremum Seeking Control

2017 ◽  
Author(s):  
Zhongyou Wu ◽  
Yaoyu Li
Keyword(s):  
Wind Turbine ◽  
Real Time ◽  
Wind Farm ◽  
Optimization Techniques ◽  
Extremum Seeking ◽  
Extremum Seeking Control ◽  
Energy Capture ◽  
Time Optimization ◽  
Real Time Optimization ◽  
Nested Loop

Real-time optimization of wind farm energy capture for below rated wind speed is critical for reducing the levelized cost of energy (LCOE). Performance of model based control and optimization techniques can be significantly limited by the difficulty in obtaining accurate turbine and farm models in field operation, as well as the prohibitive cost for accurate wind measurements. The Nested-Loop Extremum Seeking Control (NLESC), recently proposed as a model free method has demonstrated its great potential in wind farm energy capture optimization. However, a major limitation of previous work is the slow convergence, for which a primary cause is the low dither frequencies used by upwind turbines, primarily due to wake propagation delay through the turbine array. In this study, NLESC is enhanced with the predictor based delay compensation proposed by Oliveira and Krstic [1], which allows the use of higher dither frequencies for upwind turbines. The convergence speed can thus be improved, increasing the energy capture consequently. Simulation study is performed for a cascaded three-turbine array using the SimWindFarm platform. Simulation results show the improved energy capture of the wind turbine array under smooth and turbulent wind conditions, even up to 10% turbulence intensity. The impact of the proposed optimization methods on the fatigue loads of wind turbine structures is also evaluated.

Optimizing Energy Capture of Cascaded Wind Turbine Array With Nested-Loop Extremum Seeking Control

2015 ◽  
Vol 137 (12) ◽  
Author(s):  
Zhongzhou Yang ◽  
Yaoyu Li ◽  
John E. Seem
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Simulation Study ◽  
Wind Farm ◽  
Extremum Seeking ◽  
Power Coefficient ◽  
Extremum Seeking Control ◽  
Energy Capture ◽  
Principle Of Optimality ◽  
Nested Loop

This paper proposes a nested-loop extremum seeking control (NLESC) scheme for optimizing the energy capture of wind farm that is formed by a wind turbine array along the prevailing wind direction. It has been shown in earlier work that the axial induction factors of individual wind turbines can be optimized from downstream to upstream units in a sequential manner, which is a spatial domain analogy to the principle of optimality in dynamic programing. Therefore, it is proposed to optimize the turbine operation by a nested-loop optimization framework from the downstream to upstream turbines, based on feedback of the power of the immediate turbine and its downstream units. The extremum seeking control (ESC) based on dither–demodulation scheme is selected as a model-free real-time optimization solution for the individual loops. First, the principle of optimality for optimizing wind farm energy capture is proved for the cascaded wind turbine array based on the disk model. Analysis shows that the optimal torque gain of each turbine in a cascade of turbines is invariant with wind speed if the wind direction does not change. Then, the NLESC scheme is proposed, with the array power coefficient selected as the performance index to be optimized in real-time. As changes of upstream turbine operation affect downstream turbines with significant delays due to wind propagation, a cross-covariance based delay estimate is used to improve the determination of the array power coefficient. The proposed scheme is evaluated with simulation study using a three-turbine wind farm with the simwindfarm simulation platform. Simulation study is performed under both smooth and turbulent winds, and the results indicate the convergence to the actual optimum. Also, simulation under different wind speeds supports the earlier analysis results that the optimal torque gains of the cascaded turbines are invariant to wind speed.

Maximizing Wind Farm Energy Capture via Nested-Loop Extremum Seeking Control

2013 ◽  
Author(s):  
Zhongzhou Yang ◽  
Yaoyu Li ◽  
John E. Seem
Keyword(s):  
Wind Farm ◽  
Extremum Seeking ◽  
Variable Speed ◽  
Extremum Seeking Control ◽  
Control Approach ◽  
Energy Capture ◽  
Cross Covariance ◽  
Scheme Analysis ◽  
Loop Scheme ◽  
Nested Loop

This paper proposes a novel control approach for optimizing wind farm energy capture with a nested-loop scheme of extremum seeking control (ESC). Similar to Bellman’s Principle of Optimality, it has been shown in earlier work that the axial induction factors of individual wind turbines can be optimized from downstream to upstream units in a sequential manner, i.e. the turbine operation can be optimized based on the power of the immediate turbine and its downstream units. In this study, this scheme is illustrated for wind turbine array with variable-speed turbines for which torque gain is controlled to vary axial induction factors. The proposed nested-loop ESC is demonstrated with a 3-turbine wind farm using the SimWindFarm simulation platform. Simulation under smooth and turbulent winds show the effectiveness of the proposed scheme. Analysis shows that the optimal torque gain of each turbine in a cascade of turbines is invariant with wind speed if the wind direction does not change, which is supported by simulation results for smooth wind inputs. As changes of upstream turbine operation affects the downstream turbines with significant delays due to wind propagation, a cross-covariance based delay estimate is proposed as adaptive phase compensation between the dither and demodulation signals.

Power Output Efficiency in Large Wind Farms with Different Streamwise Turbine Spacing

2020 ◽  
Author(s):  
Yu-Ting Wu ◽  
Yu-Hsiang Tsao
Keyword(s):  
Power Output ◽  
Wind Farm ◽  
Wind Farms ◽  
Power Production ◽  
Internal Boundary ◽  
Incoming Flow ◽  
Flow Conditions ◽  
Inflow Condition ◽  
High Turbulence ◽  
Large Wind

<p>A large-eddy simulation (LES) model, coupled with a dynamic actuator-disk model, is used to investigate the turbine power production and the turbine wake distribution in large wind farms where the streamwise turbine spacing of 7, 9, 12, 15, and 18 rotor diameters are considered. Two incoming flow conditions, three wind turbine arrangements, as well as the five turbine spacings are involved in this study, which leads to a total of 30 LES wind farm scenarios. The two incoming flow conditions have the same mean velocity of 9 m s<sup>-1</sup> but different turbulence intensity levels (i.e., 7% and 11%) at the hub height level. The considered turbine arrangements are the perfectly-aligned, laterally-staggered, and vertically-staggered layouts. The simulated results show that the turbine power production has a significant improvement by increasing the streamwise turbine spacing. With increasing the streamwise turbine spacing from 7 to 18 rotor diameters, the overall averaged power outputs are raised by about 27% in the staggered wind farms and about 38% in the aligned wind farms. The wind farm scenarios with the turbine spacing of 12d or greater in a large wind farm can lead to an increasing trend in the power production from the downstream turbines in the high-turbulence inflow condition, or also avoids the degradation of the power output on the turbines with the low-turbulence inflow condition. The flow adjustment above the wind farm results in the generation of the internal boundary layer (IBL), which grows up vertically along with the wake-wise direction. The growth of the IBL is found to be affected by the changes in the inflow condition and the turbine spacing. The IBL depth above the wind farms is found to be influenced by the turbine spacing, whereas the IBL depth in the downstream wake region of the wind farms shows a rapid increase under the high-turbulence inflow condition.</p>

Maximizing Wind Turbine Energy Capture via Extremum Seeking Control

2008 ◽  
Author(s):  
Justin Creaby ◽  
Yaoyu Li ◽  
John E. Seem
Keyword(s):  
Wind Turbine ◽  
Torque Control ◽  
Extremum Seeking ◽  
Control Torque ◽  
Pass Filter ◽  
Extremum Seeking Control ◽  
Energy Capture ◽  
Variable Speed Wind Turbine ◽  
Speed Up ◽  
High Pass

Maximizing wind turbine energy capture has become an important issue as more turbines are installed in low wind areas. This paper investigates the application of extremum seeking control (ESC) to maximizing the energy capture of variable speed wind turbine. The optimal control torque and pitch angle are searched via ESC based on the measurement of output power. The advantage is the independency from accurate wind measurement. Simulation has been conducted on FAST for a wind turbine dynamic model, under uniformly steady wind, stair-case wind speed variations, and turbulence wind. The simulation results indicated that the captured power increased by up to 4% over the standard torque control. Anti-windup ESC was then applied to overcome the actuation saturation which may disable the ESC process. Finally, the ESC with high-pass filter input resetting was applied to speed up the transient under abrupt change of wind.

scholarly journals Distributed Extremum-Seeking for Wind Farm Power Maximization Using Sliding Mode Control

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 828
Author(s):  
Yasser Bin Salamah ◽  
Umit Ozguner
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Sliding Mode ◽  
Wind Farms ◽  
Extremum Seeking ◽  
Consensus Algorithm ◽  
Total Power ◽  
Model Free ◽  
Optimal Set ◽  
Distributed Scheme

This paper introduces a sliding-mode-based extremum-seeking algorithm aimed at generating optimal set-points of wind turbines in wind farms. A distributed extremum-seeking control is directed to fully utilize the captured wind energy by taking into consideration the wake and aerodynamic properties between wind turbines. The proposed approach is a model-free algorithm. Namely, it is independent of the model selection of the wake interaction between the wind turbines. The proposed distributed scheme consists of two parts. A dynamic consensus algorithm and an extremum-seeking controller based on sliding-mode theory. The distributed consensus algorithm is exploited to estimate the value of the total power produced by a wind farm. Subsequently, sliding-mode extremum-seeking controllers are intended to cooperatively produce optimal set-points for wind turbines within the farm. Scheme performance is tested via extensive simulations under both steady and varying wind speed and directions. The presented distributed scheme is compared with a centralized approach, in which the problem can be seen as a multivariable optimization. The results show that the employed scheme is able to successfully maximize power production in wind farms.

Maximizing Wind Turbine Energy Capture Using Multivariable Extremum Seeking Control

2009 ◽  
Vol 33 (4) ◽  
pp. 361-387 ◽  
Author(s):  
Justin Creaby ◽  
Yaoyu Li ◽  
John E. Seem
Keyword(s):  
Wind Turbine ◽  
Extremum Seeking ◽  
Extremum Seeking Control ◽  
Energy Capture

scholarly journals Sensitivity and Uncertainty of the FLORIS Model Applied on the Lillgrund Wind Farm

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1293
Author(s):  
Maarten T. van Beek ◽  
Axelle Viré ◽  
Søren J. Andersen
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Energy Gain ◽  
Control Technique ◽  
Model Parameter ◽  
Aerodynamic Interaction ◽  
Efficiency Losses ◽  
Improved Performance ◽  
Inflow Conditions ◽  
Low Uncertainty

Wind farms experience significant efficiency losses due to the aerodynamic interaction between turbines. A possible control technique to minimize these losses is yaw-based wake steering. This paper investigates the potential for improved performance of the Lillgrund wind farm through a detailed calibration of a low-fidelity engineering model aimed specifically at yaw-based wake steering. The importance of each model parameter is assessed through a sensitivity analysis. This work shows that the model is overparameterized as at least one model parameter can be excluded from the calibration. The performance of the calibrated model is tested through an uncertainty analysis, which showed that the model has a significant bias but low uncertainty when comparing the predicted wake losses with measured wake losses. The model is used to optimize the annual energy production of the Lillgrund wind farm by determining yaw angles for specific inflow conditions. A significant energy gain is found when the optimal yaw angles are calculated deterministically. However, the energy gain decreases drastically when uncertainty in input conditions is included. More robust yaw angles can be obtained when the input uncertainty is taken into account during the optimization, which yields an energy gain of approximately 3.4%.

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