five

Onshore wind generation time series for technology SP335 HH150 at resource grade C (PECD 2021 update)

收藏
data.dtu.dk2023-07-12 更新2025-03-25 收录
下载链接:
https://data.dtu.dk/articles/dataset/Onshore_wind_generation_time_series_for_technology_SP335_HH150_at_resource_grade_C_PECD_2021_update_/19689046/1
下载链接
链接失效反馈
官方服务:
资源简介:
This data (csv file) provides simulated hourly time series of onshore wind generation with specific power (SP) 335 W/m2 turbines at hub height (HH) of 150 m for the regions shown in the attached map. The analysed wind power plants are sited at the 50 % lowest mean wind speed locations in each region, i.e., in resource grade (RG) C. The map shows the resulting capacity factors (annual mean). The Excel file gives a rough indication if this wind technology is suitable for the different regions for this RG or not. The available land considers all onshore land area of a region, except lakes, cities, and very high elevation locations. The possible impact of any existing onshore wind installations in the region is not considered. Wake losses are modeled, with additional 5 % of other losses and unavailability considered. The time stamps are in GMT; the variable (column) names relate to the region names shown in the maps. The data include also country-level aggregations, e.g., UK00 is the aggregated onshore wind generation of all the UK regions (weighted by regional installed capacities). The data are part of the variable renewable energy generation time series created for ENTSO-E in the 2021 update of the Pan-European Climate Database (PECD) dataset. ENTSO-E has used the data in ERAA 2021 and Winter Outlook 2021-2022 assessments, and they are used in TYNDP 2022. The simulations are carried out by DTU Wind Energy, with the future technology selection and data validation discussed and agreed with ENTSO-E and its members. The linked journal paper (1st link) describes the simulation methodology (combination of ERA5 and GWA data is used). It is requested that the paper is cited when the data are used. The linked related journal paper (2nd link) describes the concept of resource grades and how they can be applied in energy system analyses.  This item is part of a larger collection of wind and solar data: https://doi.org/10.11583/DTU.c.5939581

本数据集(CSV文件)提供了模拟的每小时时序数据,数据涉及陆上风电场在特定功率(SP)为335 W/m2的风机轮毂高度(HH)150 m处的发电情况。所分析的风电场位于各区域50%最低平均风速的位置,即资源等级(RG)C级。附图展示了由此产生的容量系数(年平均值)。Excel文件为判断该风电技术在资源等级C级是否适用于不同区域提供了大致的参考。考虑的土地面积包括该区域的全部陆上区域,但排除湖泊、城市和极高海拔地区。未考虑该区域现有陆上风电场可能产生的任何影响。模型中考虑了尾流损失,并额外考虑了5%的其他损失和不可用性。时间戳以GMT为基准;变量(列)名称与地图上所示的区域名称相对应。数据还包括国家层面的汇总,例如,UK00表示英国所有区域的陆上风电发电量总和(按区域装机容量加权)。这些数据是专为ENTSO-E在2021年更新的泛欧洲气候数据库(PECD)数据集创建的可变可再生能源发电时序数据的一部分。ENTSO-E已使用这些数据在ERAA 2021和冬季展望2021-2022评估中使用,并在TYNDP 2022中使用。模拟由DTU Wind Energy执行,未来技术选择和数据验证已与ENTSO-E及其成员讨论并达成一致。相关联的期刊论文(第1个链接)描述了模拟方法(使用了ERA5和GWA数据的组合)。在使用数据时,请引用该论文。相关联的期刊论文(第2个链接)描述了资源等级的概念及其在能源系统分析中的应用。该数据项是风能和太阳能数据更大集合的一部分:https://doi.org/10.11583/DTU.c.5939581。
提供机构:
data.dtu.dk
二维码
社区交流群
二维码
科研交流群
商业服务