Wind farm cooperative control for optimal power generation

Wang, Fa; García-Sanz, Mario

doi:10.1177/0309524x18780377

Cited by 14 publications

(10 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [12], the problem of zero-point shifting of the yaw position was studied using SCADA data: an indicator was proposed for evaluating the power performance at each yaw angle, and it was used for the diagnosis of yaw misalignment. Also, the yawing behavior of wind turbines at the wind farm level has recently become a very important subject in the wind energy literature as regards cooperative wind turbine control [13][14][15] and wake steering. For example, in [16][17][18][19], the wake deviation in relation to yaw misalignment was studied.…”

Section: Introductionmentioning

confidence: 99%

A Study of the Impact of Pitch Misalignment on Wind Turbine Performance

Astolfi

2019

Machines

View full text Add to dashboard Cite

Pitch angle control is the most common means of adjusting the torque of wind turbines. The verification of its correct function and the optimization of its control are therefore very important for improving the efficiency of wind kinetic energy conversion. On these grounds, this work is devoted to studying the impact of pitch misalignment on wind turbine power production. A test case wind farm sited onshore, featuring five multi-megawatt wind turbines, was studied. On one wind turbine on the farm, a maximum pitch imbalance between the blades of 4.5 ° was detected; therefore, there was an intervention for recalibration. Operational data were available for assessing production improvement after the intervention. Due to the non-stationary conditions to which wind turbines are subjected, this is generally a non-trivial problem. In this work, a general method was formulated for studying this kind of problem: it is based on the study, before and after the upgrade, of the residuals between the measured power output and a reliable model of the power output itself. A careful formulation of the model is therefore crucial: in this work, an automatic feature selection algorithm based on stepwise multivariate regression was adopted, and it allows identification of the most meaningful input variables for a multivariate linear model whose target is the power of the wind turbine whose pitch has been recalibrated. This method can be useful, in general, for the study of wind turbine power upgrades, which have been recently spreading in the wind energy industry, and for the monitoring of wind turbine performances. For the test case of interest, the power of the recalibrated wind turbine is modeled as a linear function of the active and reactive power of the nearby wind turbines, and it is estimated that, after the intervention, the pitch recalibration provided a 5.5% improvement in the power production below rated power. Wind turbine practitioners, in general, should pay considerable attention to the pitch imbalance, because it increases loads and affects the residue lifetime; in particular, the results of this study indicate that severe pitch misalignment can heavily impact power production.

show abstract

Section: Introductionmentioning

confidence: 99%

A Study of the Impact of Pitch Misalignment on Wind Turbine Performance

Astolfi

2019

Machines

View full text Add to dashboard Cite

show abstract

“…For example, it is remarkable that wind turbine control optimization can be conceived at the level of each single wind turbine or at the wind farm level. This work deals with the former type of approach; nevertheless it is important to recall that cooperative control [1][2][3] and wake steering [4][5][6][7][8] are two closely related aspects, currently standing at the frontier in the wind energy research: the objective is adopting non-trivial yaw and-or pitch control strategies [9,10], in order to optimize the power production and possibly mitigate mechanical loads at the level of wind farm.…”

Section: Introductionmentioning

confidence: 99%

Wind Turbine Yaw Control Optimization and Its Impact on Performance

2019

View full text Add to dashboard Cite

The optimization of wind energy conversion efficiency has been recently boosting the technology improvement and the scientific comprehension of wind turbines. In this context, the yawing behavior of wind turbines has become a key topic: the yaw control can actually be exploited for optimization at the level of single wind turbine and of wind farm (for example, through active control of wakes). On these grounds, this work is devoted to the study of the yaw control optimization on a 2 MW wind turbine. The upgrade is estimated by analysing the difference between the measured post-upgrade power and a data driven model of the power according to the pre-upgrade behavior. Particular attention has therefore been devoted to the formulation of a reliable model for the pre-upgrade power of the wind turbine of interest, as a function of the operation variables of all the nearby wind turbines in the wind farm: the high correlation between the possible covariates of the model indicates that Principal Component Regression (PCR) is an adequate choice. Using this method, the obtained result for the selected test case is that the yaw control optimization provides a 1% of annual energy production improvement. This result indicates that wind turbine control optimization can non-negligibly improve the efficiency of wind turbine technology.

show abstract

“…For completeness, it should be said that production optimization can be conceived also at the wind farm level and there is very interesting scientific research devoted to layout optimization [2][3][4][5][6], wind farm control [7][8][9], and yaw active control for wake interactions management [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Wind Turbine Power Curve Upgrades: Part II

Astolfi

Castellani

2019

Energies

View full text Add to dashboard Cite

Wind turbine power upgrades have recently become a debated topic in wind energy research. Their assessment poses some challenges and calls for devoted techniques: some reasons are the stochastic nature of the wind and the multivariate dependency of wind turbine power. In this work, two test cases were studied. The former is the yaw management optimization on a 2 MW wind turbine; the latter is a comprehensive control upgrade (pitch, yaw, and cut-out) for 850 kW wind turbines. The upgrade impact was estimated by analyzing the difference between the post-upgrade power and a data-driven simulation of the power if the upgrade did not take place. Therefore, a reliable model for the pre-upgrade power of the wind turbines of interest was needed and, in this work, a principal component regression was employed. The yaw control optimization was shown to provide a 1.3% of production improvement and the control re-powering provided 2.5%. Another qualifying point was that, for the 850 kW wind turbine re-powering, the data quality was sufficient for an upgrade estimate based on power curve analysis and a good agreement with the model result was obtained. Summarizing, evidence of the profitability of wind turbine power upgrades was collected and data-driven methods were elaborated for power upgrade assessment and, in general, for wind turbine performance control and monitoring.

show abstract

Wind farm cooperative control for optimal power generation

Cited by 14 publications

References 13 publications

A Study of the Impact of Pitch Misalignment on Wind Turbine Performance

A Study of the Impact of Pitch Misalignment on Wind Turbine Performance

Wind Turbine Yaw Control Optimization and Its Impact on Performance

Wind Turbine Power Curve Upgrades: Part II

Contact Info

Product

Resources

About