Initial Results From a Field Campaign of Wake Steering Applied at a Commercial Wind Farm: Part 1 (original) (raw)
Related papers
Wind Energy Science
Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to redirect their wakes away from downstream turbines, thereby increasing the net wind plant power production and reducing fatigue loads generated by wake turbulence. In this paper, we present results from a wake-steering experiment at a commercial wind plant involving two wind turbines spaced 3.7 rotor diameters apart. During the 3-month experiment period, we estimate that wake steering reduced wake losses by 5.6 % for the wind direction sector investigated. After applying a long-term correction based on the site wind rose, the reduction in wake losses increases to 9.3 %. As a function of wind speed, we find large energy improvements near cut-in wind speed, where wake steering can prevent the downstream wind turbine from shutting down. Yet for wind speeds between 6-8 m/s, we observe little change in performance with wake steering. However, wake steering was found to improve energy production significantly for below-rated wind speeds from 8-12 m/s. By measuring the relationship between yaw misalignment and power production using a nacelle lidar, we attribute much of the improvement in wake-steering performance at higher wind speeds to a significant reduction in the power loss of the upstream turbine as wind speed increases. Additionally, we find higher wind direction variability at lower wind speeds, which contributes to poor performance in the 6-8 m/s wind speed bin because of slow yaw controller dynamics. Further, we compare the measured performance of wake steering to predictions using the FLORIS (FLOw Redirection and Induction in Steady State) wind farm control tool coupled with a wind direction variability model. Although the achieved yaw offsets at the upstream wind turbine fall short of the intended yaw offsets, we find that they are predicted well by the wind direction variability model. When incorporating the expected yaw offsets, estimates of the energy improvement from wake steering using FLORIS closely match the experimental results.
Continued Results from a Field Campaign of Wake Steering Applied at a Commercial Wind Farm: Part 2
2020
This paper presents the results of a field campaign investigating the performance of wake steering applied at a section of a commercial wind farm. It is the second phase of the study for which the first phase was reported in Fleming et al. (2019). The authors implemented wake steering on two turbine pairs, and compared results with the latest FLORIS (FLOw Redirection and Induction in Steady State) model of wake steering, showing good agreement in overall energy increase. Further, although not the original intention of the study, we also used the results to detect the secondary steering phenomenon. Results show an overall reduction in wake losses of approximately 6.6 % for the regions of operation, which corresponds to achieving roughly half of the static optimal result.
Field experiment for open-loop yaw-based wake steering at a commercial onshore wind farm in Italy
The concept of wake steering on wind farms for power maximization has gained significant popularity over the last decade. Recent field trials described in the literature not only demonstrate the real potential of wake steering on commercial wind farms but also show that wake steering does not yet consistently lead to an increase in energy production for all inflow conditions. Moreover, a recent survey among experts shows that validation of the concept currently remains the largest barrier to adoption. In response, this article presents the results of a field experiment investigating wake steering in three-turbine arrays at an onshore wind farm in Italy. This experiment was performed as part of the European CL-Windcon project. While important, this experiment excludes an analysis of the structural loads and focuses solely on the effects of wake steering on power production. The measurements show increases in power production of up to 35 % for two-turbine interactions and up to 16 % for three-turbine interactions. However, losses in power production are seen for various regions of wind directions too. In addition to the gains achieved through wake steering at downstream turbines, more interesting to note is that a significant share in gains is from the upstream turbines, showing an increased power production of the yawed turbine itself compared to baseline operation for some wind directions. Furthermore, the surrogate model, while capturing the general trends of wake interaction, lacks the details necessary to accurately represent the measurements. This article supports the notion that further research is necessary, notably on the topics of wind farm modeling and experiment design, before wake steering will lead to consistent energy gains on commercial wind farms.
Wake steering of multi-rotor wind turbines: a new wind farm control strategy
arXiv: Fluid Dynamics, 2020
In this paper, wake steering is applied to multi-rotor turbines to determine whether it has the potential to reduce wind plant wake losses. Through application of rotor yaw to multi-rotor turbines, a new degree of freedom is introduced to wind farm control such that wakes can be expanded, channelled or redirected to improve inflow conditions for downstream turbines. Five different yaw configurations are investigated (including a baseline case) by employing large-eddy simulations (LES) to generate a detailed representation of the velocity field downwind of a multi-rotor wind turbine. Two lower fidelity models from single rotor yaw studies (curled-wake model and analytical Gaussian wake model) are extended to the multi-rotor case and their results are compared with the LES data. For each model, the wake is analysed primarily by examining wake cross sections at different downwind distances. Further quantitative analysis is carried out through characterisations of wake centroids and wid...
Further Study on the Effects of Wind Turbine Yaw Operation for Aiding Active Wake Management
Applied Sciences
Active wake management (AWM) via yaw control has been discussed in recent years as a potential way to improve the power production of a wind farm. In such a technique, the wind turbines will be required to work frequently at misaligned yaw angles in order to reduce the vortices in the wake area behind the turbines. However, today, it is still not very clear about how yaw operation affects the dynamics and power generation performance of the wind turbines. To further understand the effects of yaw operation, numerical research is conducted in this paper. In the study, the optimal size of the flow field used in the computational fluid dynamics (CFD) calculation was specifically discussed in order to obtain an efficient numerical model to quickly and accurately predict the dynamics and the performance of the turbines. Through this research, the correlation between the blade loads during yaw and non-yaw operations is established for aiding yaw control, and the blade loads and power gener...
Field investigation on the influence of yaw misalignment on the propagation of wind turbine wakes
Wind Energy, 2018
A comprehensive understanding of the wake development of wind turbines is essential for improving the power yield of wind farms and for reducing the structural loading of the turbines. Reducing the overall negative impact of wake flows on individual turbines in a farm is one goal of wind farm control. We aim to demonstrate the applicability of yaw control for deflecting wind turbine wakes in a full-scale field experiment. For this purpose, we conducted a measurement campaign at a multimegawatt onshore wind turbine including inflow and wake flow measurements using ground-and nacelle-based long-range light detection and ranging devices. Yaw misalignments of the turbine with respect to the inflow direction of up to 20 • were investigated. We were able to show that under neutral atmospheric conditions, these turbine misalignments cause lateral deflections of its wake. Larger yaw misalignments resulted in greater wake deflection. Because of the inherent struggle in capturing complex and highly dynamic ambient conditions in the field using a limited number of sensors, we particularly focused on providing a comprehensive and comprehensible description of the measurement setup, including the identification of potential uncertainties.
Experimental investigation of wake effects on wind turbine performance
Renewable Energy, 2011
The wake interference effect on the performance of a downstream wind turbine was investigated experimentally. Two similar model turbines with the same rotor diameter were used. The effects on the performance of the downstream turbine of the distance of separation between the turbines and the amount of power extracted from the upstream turbine were studied. The effects of these parameters on the total power output from the turbines were also estimated. The reduction in the maximum power coefficient of the downstream turbine is strongly dependent on the distance between the turbines and the operating condition of the upstream turbine. Depending on the distance of separation and blade pitch angle, the loss in power from the downstream turbine varies from about 20 to 46% compared to the power output from an unobstructed single turbine operating at its designed conditions. By operating the upstream turbine slightly outside this optimum setting or yawing the upstream turbine, the power output from the downstream turbine was significantly improved. This study shows that the total power output could be increased by installing an upstream turbine which extracts less power than the following turbines. By operating the upstream turbine in yawed condition, the gain in total power output from the two turbines could be increased by about 12%.
Wind tunnel testing of wake steering with dynamic wind direction changes
The performance of an open-loop wake-steering controller is investigated with a new unique set of wind tunnel experiments. A cluster of three scaled wind turbines, placed on a large turntable, is exposed to a turbulent inflow and dynamically changing wind directions, resulting in dynamically varying wake interactions. The changes in wind direction were sourced and scaled from a field-measured time history and mirrored onto the movement of the turntable. Exploiting the known, repeatable, and controllable conditions of the wind tunnel, this study investigates the following effects: fidelity of the model used for synthesizing the controller, assumption of steady-state vs. dynamic plant behavior, wind direction uncertainty, the robustness of the formulation in regard to this uncertainty, and a finite yaw rate. The results were analyzed for power production of the cluster, fatigue loads, and yaw actuator duty cycle. The study highlights the importance of using a robust formulation and plant flow models of appropriate fidelity and the existence of possible margins for improvement by the use of dynamic controllers.
Wake Management in Wind Farms: An Adaptive Control Approach
Energies
Advanced wind measuring systems like Light Detection and Ranging (LiDAR) is useful for wake management in wind farms. However, due to uncertainty in estimating the parameters involved, adaptive control of wake center is needed for a wind farm layout. LiDAR is used to track the wake center trajectory so as to perform wake control simulations, and the estimated effective wind speed is used to model wind farms in the form of transfer functions. A wake management strategy is proposed for multi-wind turbine system where the effect of upstream turbines is modeled in form of effective wind speed deficit on a downstream wind turbine. The uncertainties in the wake center model are handled by an adaptive PI controller which steers wake center to desired value. Yaw angle of upstream wind turbines is varied in order to redirect the wake and several performance parameters such as effective wind speed, velocity deficit and effective turbulence are evaluated for an effective assessment of the appr...