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  • 标题:Predictive mapping of the global power system using open data
  • 本地全文:下载
  • 作者:C. Arderne ; C. Zorn ; C. Nicolas
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2020
  • 卷号:7
  • 期号:1
  • 页码:1-12
  • DOI:10.1038/s41597-019-0347-4
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:Limited data on global power infrastructure makes it difficult to respond to challenges in electricity access and climate change.Although high-voltage data on transmission networks are often available, medium- and low-voltage data are often non-existent or unavailable.This presents a challenge for practitioners working on the electricity access agenda, power sector resilience or climate change adaptation.Using state-of-the-art algorithms in geospatial data analysis, we create a first composite map of the global power system with an open license.We find that 97% of the global population lives within 10-km of a MV line, but with large variations between regions and income levels.We show an accuracy of 75% across our validation set of 14 countries, and we demonstrate the value of these data at both a national and regional level.The results from this study pave the way for improved efforts in electricity modelling and planning and are an important step in tackling the Sustainable Development Goals.
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