Axial induction controller field test at Sedini wind farm

Author:

Bossanyi Ervin,Ruisi Renzo

Abstract

Abstract. This paper describes the design and testing of an axial induction controller implemented on a row of nine turbines on the Sedini wind farm in Sardinia, Italy. This work was performed as part of the EU Horizon 2020 research project CL-Windcon. An engineering wake model, selected for its good fit to historical SCADA data from the site, was used in the LongSim code to optimise turbine power reduction setpoints for a large matrix of steady-state wind conditions. The setpoints were incorporated into a dynamic control algorithm capable of running on-site using available wind condition estimates from the turbines. The complete algorithm was tested in dynamic time-domain simulations using LongSim, using a time-varying wind field generated from historical met mast data from the site. The control algorithm was implemented on-site, with the wind farm controller toggled on and off at 35 min intervals to allow the performance with and without the controller to be compared in comparable wind conditions. Data were collected between July 2019 and early February 2020. The results have been analysed and indicate a positive increase in energy production resulting from the induction control, in line with LongSim model predictions, although a larger volume of valid data would be necessary to provide statistically robust conclusions. The measurements also provide a validation of the LongSim model, proving its value for both steady-state setpoint optimisation and time-domain simulation of wind farm performance.

Publisher

Copernicus GmbH

Subject

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

Reference18 articles.

1. Ainslie, J. F.: Calculating the flowfield in the wake of wind turbines, J. Wind Eng. Indust. Aerodynam., 27, 213–224, 1988.

2. Anderson, M.: Simplified solution to the eddy-viscosity wake model, RES technical report 01327 000202, Renewable Energy Systems Ltd., Hemel, Hempstead, 2009.

3. Bastankhah, M. and Porté-Agel, F.: Experimental and theoretical study of wind turbine wakes in yawed conditions, J. Fluid Mech., 806, 506–541, 2016.

4. Bossanyi, E., Potenza, G., Calabretta, F., Bot, E., Kanev, S., Elorza, I., Campagnolo, F., Fortes-Plaza, A., Schreiber, J., Doekemeijer, B., Eguinoa-Erdozain, I., Gomez-Iradi, S., Astrain-Juangarcia, D., Cantero-Nouqueret, E., Irigoyen-Martinez, U., Fernandes-Correia, P., Benito, P., Kern, S., Kim, Y., Raach, S., Knudsen, T., and Schito, P.: Description of the reference and the control-oriented wind farm models, CL-Windcon deliverable D1.2, available at: https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5ba664d11&appId=PPGMS, last access: 30 April 2018.

5. Campagnolo, F., Petrovi, V., Bottasso, C. L., and Croce A. Wind tunnel testing of wake control strategies, in: Proc. American Control Conference (ACC), 6–8 July 2016, Boston, USA, 513–518, 2016a.

Cited by 19 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