Quantitative comparison of power production and power quality onshore and offshore: a case study from the eastern United States

Rebecca Foody, J. Coburn, J. Aird, R. Barthelmie, S. Pryor
{"title":"Quantitative comparison of power production and power quality onshore and offshore: a case study from the eastern United States","authors":"Rebecca Foody, J. Coburn, J. Aird, R. Barthelmie, S. Pryor","doi":"10.5194/wes-9-263-2024","DOIUrl":null,"url":null,"abstract":"Abstract. A major issue in quantifying potential power generation from prospective wind energy sites is the lack of observations from heights relevant to modern wind turbines, particularly for offshore where blade tip heights are projected to increase beyond 250 m. We present analyses of uniquely detailed data sets from lidar (light detection and ranging) deployments in New York State and on two buoys in the adjacent New York Bight to examine the relative power generation potential and power quality at these on- and offshore locations. Time series of 10 min wind power production are computed from these wind speeds using the power curve from the International Energy Agency 15 MW reference wind turbine. Given the relatively close proximity of these lidar deployments, they share a common synoptic-scale meteorology and seasonal variability with lowest wind speeds in July and August. Time series of power production from the on- and offshore location are highly spatially correlated with the Spearman rank correlation coefficient dropping below 0.4 for separation distances of approximately 350 km. Hence careful planning of on- and offshore wind farms (i.e., separation of major plants by > 350 km) can be used reduce the system-wide probability of low wind energy power production. Energy density at 150 m height at the offshore buoys is more than 40 % higher, and the Weibull scale parameter is 2 m s−1 higher than at all but one of the land sites. Analyses of power production time series indicate annual energy production is almost twice as high for the two offshore locations. Further, electrical power production quality is higher from the offshore sites that exhibit a lower amplitude of diurnal variability, plus a lower probability of wind speeds below the cut-in and of ramp events of any magnitude. Despite this and the higher resource, the estimated levelized cost of energy (LCoE) is higher from the offshore sites mainly due to the higher infrastructure costs. Nonetheless, the projected LCoE is highly competitive from all sites considered.\n","PeriodicalId":509667,"journal":{"name":"Wind Energy Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wind Energy Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/wes-9-263-2024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract. A major issue in quantifying potential power generation from prospective wind energy sites is the lack of observations from heights relevant to modern wind turbines, particularly for offshore where blade tip heights are projected to increase beyond 250 m. We present analyses of uniquely detailed data sets from lidar (light detection and ranging) deployments in New York State and on two buoys in the adjacent New York Bight to examine the relative power generation potential and power quality at these on- and offshore locations. Time series of 10 min wind power production are computed from these wind speeds using the power curve from the International Energy Agency 15 MW reference wind turbine. Given the relatively close proximity of these lidar deployments, they share a common synoptic-scale meteorology and seasonal variability with lowest wind speeds in July and August. Time series of power production from the on- and offshore location are highly spatially correlated with the Spearman rank correlation coefficient dropping below 0.4 for separation distances of approximately 350 km. Hence careful planning of on- and offshore wind farms (i.e., separation of major plants by > 350 km) can be used reduce the system-wide probability of low wind energy power production. Energy density at 150 m height at the offshore buoys is more than 40 % higher, and the Weibull scale parameter is 2 m s−1 higher than at all but one of the land sites. Analyses of power production time series indicate annual energy production is almost twice as high for the two offshore locations. Further, electrical power production quality is higher from the offshore sites that exhibit a lower amplitude of diurnal variability, plus a lower probability of wind speeds below the cut-in and of ramp events of any magnitude. Despite this and the higher resource, the estimated levelized cost of energy (LCoE) is higher from the offshore sites mainly due to the higher infrastructure costs. Nonetheless, the projected LCoE is highly competitive from all sites considered.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
陆上和海上电力生产与电能质量的定量比较:美国东部的案例研究
摘要量化未来风能场址潜在发电量的一个主要问题是缺乏与现代风力涡轮机相关高度的观测数据,特别是对于叶片尖端高度预计将超过 250 米的近海风力涡轮机。我们分析了在纽约州部署的激光雷达(光探测和测距)以及在邻近的纽约湾两个浮标上的独特详细数据集,以研究这些陆上和海上地点的相对发电潜力和电能质量。利用国际能源机构 15 兆瓦参考风力涡轮机的功率曲线,根据这些风速计算出 10 分钟风力发电量的时间序列。鉴于这些激光雷达部署点相对较近,它们具有共同的同步尺度气象和季节变化,7 月和 8 月的风速最低。陆上和海上地点的发电量时间序列在空间上高度相关,在相距约 350 千米时,斯皮尔曼秩相关系数低于 0.4。因此,仔细规划陆上和海上风电场(即主要风电场之间的距离大于 350 千米)可以降低整个系统风能发电量偏低的概率。海上浮标 150 米高度处的能量密度比陆地浮标高出 40% 以上,Weibull 尺度参数比陆地浮标高出 2 m s-1,只有一个浮标除外。电力生产时间序列分析表明,两个近海地点的年发电量几乎是陆地地点的两倍。此外,近海地点的电力生产质量较高,其昼夜变化幅度较小,而且风速低于切入点的概率较低,发生任何规模的斜坡事件的概率也较低。尽管如此,由于资源较多,预计海上发电站的平准化能源成本(LCoE)较高,主要原因是基础设施成本较高。尽管如此,从所有考虑的地点来看,预计的平准化能源成本(LCoE)都极具竞争力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
On the importance of wind predictions in wake steering optimization On the power and control of a misaligned rotor – beyond the cosine law Identification of electro-mechanical interactions in wind turbines Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm Synchronised WindScanner field measurements of the induction zone between two closely spaced wind turbines
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1