Wind Speed Weibull Model Identification in Oman, and Computed Normalized Annual Energy Production (NAEP) From Wind Turbines Based on Data From Weather Stations

IF 1.8 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Osama A. Marzouk
{"title":"Wind Speed Weibull Model Identification in Oman, and Computed Normalized Annual Energy Production (NAEP) From Wind Turbines Based on Data From Weather Stations","authors":"Osama A. Marzouk","doi":"10.1002/eng2.70089","DOIUrl":null,"url":null,"abstract":"<p>Using observation records of wind speeds from weather stations in the Sultanate of Oman between 2000 and 2023, we compute estimators of the two Weibull distribution parameters (namely, the Weibull distribution's shape parameter and the Weibull distribution's scale parameter) in 10 weather station locations within eight Omani governorates. The 10 weather station locations in Oman and their corresponding governorates are Seeb (in Muscat), Salalah (in Dhofar), Buraimi (in Al Buraimi), Masirah (in Ash Sharqiyah South), Thumrait (in Dhofar), Sur (in Ash Sharqiyah South), Khasab (in Musandam), Sohar (in Sohar), Fahud (in Az Zahirah), and Saiq (in Ad Dakhiliyah). The obtained wind speed distributions at these weather stations are then used to predict the annual energy production (AEP) for a proposed reference amount of 1 MWp of wind turbine capacity, and this specific AEP is designated here by the term “normalized annual energy production (NAEP).” The direction of the wind is also analyzed statistically over the same period to identify the more probable wind directions. Four locations were clearly distinguishable as being windy compared to the others. The simulated probability of exceeding a feasible 6 m/s (21.6 km/h) wind speed in these locations is 41.71% in Thumrait, 37.77% in Masirah, 29.53% in Sur, and 17.03% in Fahud. The NAEP values in these four locations are estimated as 1.727 GWh/MWp/year, 1.419 GWh/MWp/year, 1.038 GWh/MWp/year, and 0.602 GWh/MWp/year; respectively. The wind in the location of Thumrait is not only the fastest (on average) among the selected locations, but also the most unidirectional, blowing almost always from the south–south-east (SSE) direction; and both features make this non-coastal location in southern Oman, with an altitude of about 467 m, an attractive site for utility-scale wind farms. We also statistically analyze wind data in the port city of Duqm; and we show that the simulated probability of exceeding 6 m/s wind speed there is 24.04%, the estimated NAEP there is 0.927 GWh/MWp/year, and the wind direction there is approximately blowing from the south–south-west (SSW) direction most of the time. When compared to photovoltaic (PV) solar energy systems, onshore wind turbine systems with the same installed capacity appear to be less effective in Oman. This study closes a gap in the field of wind energy where no similar standardized NAEP as the one we propose is present.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"7 3","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.70089","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering reports : open access","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/eng2.70089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

Using observation records of wind speeds from weather stations in the Sultanate of Oman between 2000 and 2023, we compute estimators of the two Weibull distribution parameters (namely, the Weibull distribution's shape parameter and the Weibull distribution's scale parameter) in 10 weather station locations within eight Omani governorates. The 10 weather station locations in Oman and their corresponding governorates are Seeb (in Muscat), Salalah (in Dhofar), Buraimi (in Al Buraimi), Masirah (in Ash Sharqiyah South), Thumrait (in Dhofar), Sur (in Ash Sharqiyah South), Khasab (in Musandam), Sohar (in Sohar), Fahud (in Az Zahirah), and Saiq (in Ad Dakhiliyah). The obtained wind speed distributions at these weather stations are then used to predict the annual energy production (AEP) for a proposed reference amount of 1 MWp of wind turbine capacity, and this specific AEP is designated here by the term “normalized annual energy production (NAEP).” The direction of the wind is also analyzed statistically over the same period to identify the more probable wind directions. Four locations were clearly distinguishable as being windy compared to the others. The simulated probability of exceeding a feasible 6 m/s (21.6 km/h) wind speed in these locations is 41.71% in Thumrait, 37.77% in Masirah, 29.53% in Sur, and 17.03% in Fahud. The NAEP values in these four locations are estimated as 1.727 GWh/MWp/year, 1.419 GWh/MWp/year, 1.038 GWh/MWp/year, and 0.602 GWh/MWp/year; respectively. The wind in the location of Thumrait is not only the fastest (on average) among the selected locations, but also the most unidirectional, blowing almost always from the south–south-east (SSE) direction; and both features make this non-coastal location in southern Oman, with an altitude of about 467 m, an attractive site for utility-scale wind farms. We also statistically analyze wind data in the port city of Duqm; and we show that the simulated probability of exceeding 6 m/s wind speed there is 24.04%, the estimated NAEP there is 0.927 GWh/MWp/year, and the wind direction there is approximately blowing from the south–south-west (SSW) direction most of the time. When compared to photovoltaic (PV) solar energy systems, onshore wind turbine systems with the same installed capacity appear to be less effective in Oman. This study closes a gap in the field of wind energy where no similar standardized NAEP as the one we propose is present.

Abstract Image

利用 2000 年至 2023 年阿曼苏丹国气象站的风速观测记录,我们计算了阿曼八个省内 10 个气象站点的两个 Weibull 分布参数(即 Weibull 分布的形状参数和 Weibull 分布的尺度参数)的估计值。阿曼的 10 个气象站点及其对应的省份分别是:锡布(位于马斯喀特)、塞拉莱(位于佐法尔)、布莱米(位于布莱米)、马西拉(位于阿什谢尔盖南部)、图姆莱特(位于佐法尔)、苏尔(位于阿什谢尔盖南部)、哈撒布(位于穆桑达姆)、苏哈尔(位于苏哈尔)、法胡德(位于阿兹扎希拉)和赛克(位于阿达希利耶)。然后利用这些气象站获得的风速分布来预测拟议的 1 兆瓦风力涡轮机发电量参考值的年发电量 (AEP),这种特定的年发电量在此称为 "归一化年发电量 (NAEP)"。我们还对同期的风向进行了统计分析,以确定更有可能的风向。与其他地点相比,有四个地点的风向明显不同。在这些地点,超过可行的 6 米/秒(21.6 公里/小时)风速的模拟概率分别为:图姆拉特 41.71%、马西拉 37.77%、苏尔 29.53%、法胡德 17.03%。这四个地点的 NAEP 值分别为 1.727 GWh/MWp/年、1.419 GWh/MWp/年、1.038 GWh/MWp/年和 0.602 GWh/MWp/年。在所选地点中,图姆雷特的风速不仅最快(平均值),而且单向性最强,几乎总是从东南(SSE)方向吹来;这两个特点使这个位于阿曼南部、海拔约 467 米的非沿海地点成为一个具有吸引力的公用事业规模风电场地点。我们还对港口城市杜克姆的风力数据进行了统计分析;结果表明,该地风速超过 6 米/秒的模拟概率为 24.04%,NAEP 估计值为 0.927 GWh/MWp/年,而且该地大部分时间的风向近似于西南风(SSW)。与光伏太阳能系统相比,装机容量相同的陆上风力涡轮机系统在阿曼似乎不太有效。这项研究填补了风能领域的空白,因为该领域目前还没有类似于我们建议的标准化 NAEP。
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 求助全文
来源期刊
CiteScore
5.10
自引率
0.00%
发文量
0
审稿时长
19 weeks
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信