Langevin power curve analysis for numerical wind energy converter models with new insights on high frequency power performance

Abstract

Based on the Langevin equation it has been proposed to obtain power curves for wind turbines from high frequency data of wind speed measurements u(t) and power output P (t). The two parts of the Langevin approach, power curve and drift field, give a comprehensive description of the conversion dynamic over the whole operating range of the wind turbine. The method deals with high frequent data instead of 10 min means. It is therefore possible to gain a reliable power curve already from a small amount of data per wind speed. Furthermore, the method is able to visualize multiple fixed points, which is e.g. characteristic for the transition from partial to full load or in case the conversion process deviates from the standard procedures. In order to gain a deeper knowledge it is essential that the method works not only for measured data but also for numerical wind turbine models and synthetic wind fields. Here, we characterize the dynamics of a detailed numerical wind turbine model and calculate the Langevin power curve for different data samplings. We show, how to get reliable results from synthetic data and verify the applicability of the method for field measurements with ultra-sonic, cup and Lidar measurements. The independence of the fixed points on site specific turbulence effects is also confirmed with the numerical model. Furthermore, we demonstrate the potential of the Langevin approach to detect failures in the conversion process and thus show the potential of the Langevin approach for a condition monitoring system.

Normal Behaviour Models for Wind Turbine Vibrations: Comparison of Neural Networks and a Stochastic Approach

“…The cup anemometer is suitable for 1 Hz sampling, similar to previous studies [15,19,20] to analyse fatigue loads, dynamic power curves and damages on wind turbines. It turned out that this sampling frequency is indeed sufficient to resolve the response dynamics of turbine quantities with respect to the wind fluctuations.…”

Fatigue Load Estimation through a Simple Stochastic Model

“…Together with most of the properties measured at wind turbines, wind speed and torque have typically fluctuations occurring at different time spans, defining the series of increments, whose statistics describe the intermittency observed in the wind energy production [10]. In the particular case of the torque, the succession of torque increments is related to the so-called random load cycles, which are of importance for estimating fatigue loads.…”

“…See [12] for a review. In the context of wind energy, this framework has shown the ability to predict power curves of single wind turbines [10,13,14], as well as of equivalent power curves for entire wind farms [15] and, also, to properly reproduce the increment statistics of power and torque in single wind turbines [9,10].…”

“…The approach used there follows from the method proposed in [3,10] for the power output of singl turbines.…”

Variability of the Wind Turbine Power Curve

“…Indeed, instantaneous values of wind speed v(t) and wind power P(t) exhibit significant scatter about the mean profile ( Figure 1). Several studies [4][5][6][7][8] have focused on the factors contributing to this variability, including turbulent fluctuations, wind shear, directional shear, directional fluctuations, etc., with the aim of accurately modeling the "mean" profile of the wind turbine power curve [9][10][11][12].…”