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.

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.

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.

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.

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.

scholarly journals Hybrid soft computing control strategies for improving the energy capture of a wind farm

2012 ◽  
Vol 16 (suppl. 2) ◽  
pp. 483-491 ◽  
Author(s):  
Predrag Zivkovic ◽  
Vlastimir Nikolic ◽  
Gradimir Ilic ◽  
Zarko Cojbasic ◽  
Ivan Ciric
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Control Loop ◽  
Electric Generator ◽  
Energy Capture ◽  
Wind Turbine Control ◽  
Speed Estimator

In this paper, a fuzzy controller is proposed for wind turbine control. A model is analyzed and combined with a stochastic wind model for simulation purposes. Based on the model, a fuzzy control of wind turbine is developed. Wind turbine control loop provides the reference inputs for the electric generator control loop in order to make the system run with maximum power. Since the wind speed involved in the aerodynamic equations is a stochastic variable, whose effective value cannot be measured directly, a wind speed estimator is also proposed.

scholarly journals Assessment of the apparent performance characterization along with levelized cost of energy of wind power plants considering real data

2018 ◽  
Vol 36 (6) ◽  
pp. 1708-1728 ◽  
Author(s):  
Zahid H Hulio ◽  
Wei Jiang
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Power Plants ◽  
Wind Farm ◽  
Power Coefficient ◽  
Speed Ratio ◽  
Data Set ◽  
Levelized Cost ◽  
Cost Of Energy

Pakistan pursued the renewable energy policy to minimize the cost of energy per kWh as well as dependence on costly imported oil. Jhimpir site is termed as wind corridor and has tremendous proven wind power potential. The site is hosted for the first installed wind power plant. The aim of paper is to investigate the performance and levelized cost of energy of a wind farm. The methodology covers assessment of wind characteristics, performance function and levelized cost of energy model. The measured mean wind speed was found to be 8 m/s at 80 m above the ground level. The average values of standard deviation, Weibull k and c parameters, obtained using entire data set, were found to be 2.563, 3.360 and 8.940 m/s at 80 m. Performance assessment including technical, real availability and average capacity factor was found to be 97, 90 and 34.50%, respectively. It is evident that the power coefficient dropped if wind speed crosses the rated power. So it can be concluded that the efficiency of wind turbine decreased by increased wind speed. Tip speed ratio shows that a wind turbine operating close to optimal lift and drag will exhibit the performance level. Wind turbine performs better at the wind speed between 6 and 10 m/s. The estimated average levelized cost of energy was US $0.11371 and US $0.04092/kWh for 1–10 and 11–20 years, respectively. This makes it competitive in terms of low production cost per kWh to other energy technologies.

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

Power-setpoint extremum seeking control for maximizing wind power capture of turbine and farm operation

2020 ◽  
pp. 0309524X2097991
Author(s):  
Devesh Kumar ◽  
Yaoyu Li ◽  
Zhongyou Wu
Keyword(s):  
Control Strategy ◽  
Extremum Seeking ◽  
Power Demand ◽  
Extremum Seeking Control ◽  
Energy Capture ◽  
Model Free ◽  
Free Region ◽  
Power Capture ◽  
Back Calculation ◽  
Nested Loop

In this paper, we propose a power-setpoint based Extremum Seeking Control (ESC) framework for model-free Region-2 controls for maximizing the power capture for turbine and farm operation, without dependency on wind measurement. As a major obstacle for retrofitting wind turbine/farm controls is that only the power setpoint is accessible, the power-setpoint based ESC framework is proposed with a back-calculation anti-windup structure. If increasing the power demand cannot further increase actual power output, the anti-windup structure automatically holds the power demand setpoint. For farm operation, the proposed method is integrated into the Delay-compensated Nested-loop ESC. The proposed method is evaluated by simulations on the SimWindFarm platform for both single-turbine and farm operation scenarios. The results demonstrate the capability of tracking the achievable optimum power for turbine and farm operation, with only reasonable increase of some loads. The proposed method promises an easy-to-implement model-free retrofitting control strategy for enhancing wind energy capture.

scholarly journals Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2319
Author(s):  
Hyun-Goo Kim ◽  
Jin-Young Kim
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Free Stream ◽  
Turbine Blades ◽  
Wind Farms ◽  
Lidar Measurement ◽  
Wind Turbine Blades ◽  
Wake Effect

This study analyzed the performance decline of wind turbine with age using the SCADA (Supervisory Control And Data Acquisition) data and the short-term in situ LiDAR (Light Detection and Ranging) measurements taken at the Shinan wind farm located on the coast of Bigeumdo Island in the southwestern sea of South Korea. Existing methods have generally attempted to estimate performance aging through long-term trend analysis of a normalized capacity factor in which wind speed variability is calibrated. However, this study proposes a new method using SCADA data for wind farms whose total operation period is short (less than a decade). That is, the trend of power output deficit between predicted and actual power generation was analyzed in order to estimate performance aging, wherein a theoretically predicted level of power generation was calculated by substituting a free stream wind speed projecting to a wind turbine into its power curve. To calibrate a distorted wind speed measurement in a nacelle anemometer caused by the wake effect resulting from the rotation of wind-turbine blades and the shape of the nacelle, the free stream wind speed was measured using LiDAR remote sensing as the reference data; and the nacelle transfer function, which converts nacelle wind speed into free stream wind speed, was derived. A four-year analysis of the Shinan wind farm showed that the rate of performance aging of the wind turbines was estimated to be −0.52%p/year.

Experimental Study of Vertical Axis Wind Turbine with Wind Speed Self-Adapting

2012 ◽  
Vol 215-216 ◽  
pp. 1323-1326
Author(s):  
Ming Wei Xu ◽  
Jian Jun Qu ◽  
Han Zhang
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Velocity ◽  
Vertical Axis ◽  
Maximum Power ◽  
The Self ◽  
Power Coefficient ◽  
Speed Ratio ◽  
Vertical Axis Wind Turbine ◽  
Opening And Closing

A small vertical axis wind turbine with wind speed self-adapting was designed. The diameter and height of the turbine were both 0.7m. It featured that the blades were composed of movable and fixed blades, and the opening and closing of the movable blades realized the wind speed self-adapting. Aerodynamic performance of this new kind turbine was tested in a simple wind tunnel. Then the self-starting and power coefficient of the turbine were studied. The turbine with load could reliably self-start and operate stably even when the wind velocity was only 3.6 m/s. When the wind velocity was 8 m/s and the load torque was 0.1Nm, the movable blades no longer opened and the wind turbine realized the conversion from drag mode to lift mode. With the increase of wind speed, the maximum power coefficient of the turbine also improves gradually. Under 8 m/s wind speed, the maximum power coefficient of the turbine reaches to 12.26%. The experimental results showed that the new turbine not only improved the self-starting ability of the lift-style turbine, but also had a higher power coefficient in low tip speed ratio.

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