Increase a real wind farm productivity through optimizing wind turbines layout

Author:

Wang Zilu1ORCID,Zhang Bowen1,Chen Meng1,Luo Zhaohui1,Wang Longyan12ORCID

Affiliation:

1. Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, China

2. School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology, Brisbane, QLD, Australia

Abstract

In this paper, a 3D wake model considering both axial and radial wind speed variations along the incoming wind direction, and the non-flat topography effect on the wind flow, is developed for the layout optimization of a real onshore wind farm. The effectiveness of two methods (i.e., the discretization method that divides the wind scenario into small intervals and the Monte Carlo method which randomly generates the discrete wind speed samples), for evaluating the overall wind farm power production under the wind speed variation of Weibull distribution is investigated for the comparative study. It is found that the Monte Carlo power evaluation method achieves a better outcome than the traditional discretization method, with more total power output and less computational cost. Through the layout optimization with a total of 15 wind turbines installed, the individual wind turbine yields more than 533 kW power out of 536 kW theoretical wake-free power. As the installed wind turbine number increases, the maximum discrepancy of the actual wind turbine power output with respect to the theoretical power increases from 3 kW (with 15 wind turbines) to 6 kW (with 20 wind turbines). Through the comparative study of different wind rotation scenarios, it is found that the maximum discrepancy of individual actual wind turbine power outputs is 8 kW and 13 kW for a rotational angle of [Formula: see text] and [Formula: see text], respectively. Under the scenario of [Formula: see text] wind rotation scenario, the maximum individual power output deficit with 20 installed wind turbines is around 20 kW and the discrepancy of the total power output by comparing to the baseline wind model is maximally 1% proving the robustness of the optimization results with respect to the wind scenario variation.

Funder

National Natural Science Foundation of China

Postdoctoral Science Foundation of Jiangsu Province

High-level Talent Research Foundation of Jiangsu University

Publisher

SAGE Publications

Subject

Mechanical Engineering,Energy Engineering and Power Technology

Reference46 articles.

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