FarmConners wind farm flow control benchmark – Part 1: Blind test results

Author:

Göçmen TuhfeORCID,Campagnolo FilippoORCID,Duc Thomas,Eguinoa IreneORCID,Andersen Søren JuhlORCID,Petrović VlahoORCID,Imširović Lejla,Braunbehrens Robert,Liew JaimeORCID,Baungaard MadsORCID,van der Laan Maarten PaulORCID,Qian Guowei,Aparicio-Sanchez MariaORCID,González-Lope RubénORCID,Dighe Vinit V.ORCID,Becker MarcusORCID,van den Broek Maarten J.ORCID,van Wingerden Jan-WillemORCID,Stock Adam,Cole Matthew,Ruisi Renzo,Bossanyi Ervin,Requate Niklas,Strnad Simon,Schmidt Jonas,Vollmer Lukas,Sood IshaanORCID,Meyers JohanORCID

Abstract

Abstract. Wind farm flow control (WFFC) is a topic of interest at several research institutes and industry and certification agencies worldwide. For reliable performance assessment of the technology, the efficiency and the capability of the models applied to WFFC should be carefully evaluated. To address that, the FarmConners consortium has launched a common benchmark for code comparison under controlled operation to demonstrate its potential benefits, such as increased power production. The benchmark builds on available data sets from previous field campaigns, wind tunnel experiments, and high-fidelity simulations. Within that database, four blind tests are defined and 13 participants in total have submitted results for the analysis of single and multiple wakes under WFFC. Here, we present Part I of the FarmConners benchmark results, focusing on the blind tests with large-scale rotors. The observations and/or the model outcomes are evaluated via direct power comparisons at the upstream and downstream turbine(s), as well as the power gain at the wind farm level under wake steering control strategy. Additionally, wake loss reduction is also analysed to support the power performance comparison, where relevant. The majority of the participating models show good agreement with the observations or the reference high-fidelity simulations, especially for lower degrees of upstream misalignment and narrow wake sector. However, the benchmark clearly highlights the importance of the calibration procedure for control-oriented models. The potential effects of limited controlled operation data in calibration are particularly visible via frequent model mismatch for highly deflected wakes, as well as the power loss at the controlled turbine(s). In addition to the flow modelling, the sensitivity of the predicted WFFC benefits to the turbine representation and the implementation of the controller is also underlined. The FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control settings, and model complexities for the (initial) assessment of farm flow control benefits. It forms an important basis for more detailed benchmarks in the future with extended control objectives to assess the true value of WFFC.

Funder

Horizon 2020

Publisher

Copernicus GmbH

Subject

Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

Reference109 articles.

1. Ahmad, T., Coupiac, O., Petit, A., Guignard, S., Girard, N., Kazemtabrizi, B., and Matthews, P.: Field Implementation and Trial of Coordinated Control of Wind Farms, IEEE T. Sustain. Energ., 9, 1169–1176, https://doi.org/10.1109/TSTE.2017.2774508, 2017. a

2. Ainslie, J.: Calculating the flowfield in the wake of wind turbines, J. Wind Eng. Ind. Aerod., 27, 213–224, https://doi.org/10.1016/0167-6105(88)90037-2, 1988. a, b

3. Allaerts, D. and Meyers, J.: Large eddy simulation of a large wind-turbine array in a conventionally neutral atmospheric boundary layer, Phys. Fluids, 27, 065108, https://doi.org/10.1063/1.4922339, 2015. a, b, c

4. Andersen, S., Madariaga, A., Merz, K., Meyers, J., Munters, W., and Rodriguez, C.: Reference Wind Power Plant D1.03, Deliverable of EU H2020 TotalControl Project no. 727680, https://backend.orbit.dtu.dk/ws/portalfiles/portal/164663085/TotalControl_D1_03_Reference_Wind_Farm.pdf (last access: 21 July 2022), 2018. a

5. Andersen, S. J. and Troldborg, N.: Description of TotalControl Reference Wind Farm Simulations, DTU [data set], https://doi.org/10.11583/DTU.13160606.v2, 2020. a

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3