A global dataset of the cost of capital for renewable energy projects.

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Bjarne Steffen, Florian Egli, Anurag Gumber, Mak Ðukan, Paul Waidelich
{"title":"A global dataset of the cost of capital for renewable energy projects.","authors":"Bjarne Steffen, Florian Egli, Anurag Gumber, Mak Ðukan, Paul Waidelich","doi":"10.1038/s41597-025-05912-x","DOIUrl":null,"url":null,"abstract":"<p><p>The cost of capital (CoC) critically influences the levelized cost of renewable energy and, by extension, the global low-carbon transition. However, reliable and consistent CoC data remain scarce, limiting an appropriate reflection of CoC differences in energy system and integrated assessment models. We present a global dataset of CoC for renewable energy projects, covering 68 countries from 2010 to 2022 and focusing on three key technologies: utility-scale solar photovoltaics, onshore wind, and offshore wind. We systematically compile and standardize data from academic literature and international organizations, ensuring methodological comparability. Our dataset includes 1,429 data points, of which 366 provide nominal, after-tax weighted average cost of capital values. We conduct technical validation through cross-technology comparisons, temporal consistency checks, and source triangulation. By addressing a key data gap, this dataset aims to support evidence-based energy policy analysis and advance the understanding of how financing conditions impact renewable energy costs globally.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"1624"},"PeriodicalIF":6.9000,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-025-05912-x","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

The cost of capital (CoC) critically influences the levelized cost of renewable energy and, by extension, the global low-carbon transition. However, reliable and consistent CoC data remain scarce, limiting an appropriate reflection of CoC differences in energy system and integrated assessment models. We present a global dataset of CoC for renewable energy projects, covering 68 countries from 2010 to 2022 and focusing on three key technologies: utility-scale solar photovoltaics, onshore wind, and offshore wind. We systematically compile and standardize data from academic literature and international organizations, ensuring methodological comparability. Our dataset includes 1,429 data points, of which 366 provide nominal, after-tax weighted average cost of capital values. We conduct technical validation through cross-technology comparisons, temporal consistency checks, and source triangulation. By addressing a key data gap, this dataset aims to support evidence-based energy policy analysis and advance the understanding of how financing conditions impact renewable energy costs globally.

可再生能源项目的全球资本成本数据集。
资本成本严重影响可再生能源的平准化成本,进而影响全球低碳转型。然而,可靠和一致的CoC数据仍然稀缺,限制了能源系统和综合评估模型中CoC差异的适当反映。我们提供了一个全球可再生能源项目的CoC数据集,涵盖了68个国家,从2010年到2022年,重点关注三个关键技术:公用事业规模的太阳能光伏发电、陆上风能和海上风能。我们系统地汇编和标准化来自学术文献和国际组织的数据,确保方法上的可比性。我们的数据集包括1,429个数据点,其中366个提供名义税后加权平均资本成本值。我们通过跨技术比较、时间一致性检查和源三角测量进行技术验证。通过解决关键数据缺口,该数据集旨在支持基于证据的能源政策分析,并促进对融资条件如何影响全球可再生能源成本的理解。
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
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
×
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:604180095
Book学术官方微信