Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
Laboratoire des Sciences du Climate et de l'Environnement LSCE, Orme de Merisiers, 91191, Gif-sur-Yvette, France.
Sci Data. 2023 Apr 17;10(1):217. doi: 10.1038/s41597-023-02094-2.
We constructed a frequently updated, near-real-time global power generation dataset: CarbonMonitor-Power since January, 2016 at national levels with near-global coverage and hourly-to-daily time resolution. The data presented here are collected from 37 countries across all continents for eight source groups, including three types of fossil sources (coal, gas, and oil), nuclear energy and four groups of renewable energy sources (solar energy, wind energy, hydro energy and other renewables including biomass, geothermal, etc.). The global near-real-time power dataset shows the dynamics of the global power system, including its hourly, daily, weekly and seasonal patterns as influenced by daily periodical activities, weekends, seasonal cycles, regular and irregular events (i.e., holidays) and extreme events (i.e., the COVID-19 pandemic). The CarbonMonitor-Power dataset reveals that the COVID-19 pandemic caused strong disruptions in some countries (i.e., China and India), leading to a temporary or long-lasting shift to low carbon intensity, while it had only little impact in some other countries (i.e., Australia). This dataset offers a large range of opportunities for power-related scientific research and policy-making.
我们构建了一个频繁更新的、近乎实时的全球发电数据集:CarbonMonitor-Power,自 2016 年 1 月以来,在国家层面上实现了近乎全球的覆盖范围和小时到每日的时间分辨率。这里呈现的数据是从七大洲的 37 个国家收集的,涵盖了八个来源组,包括三种化石燃料(煤炭、天然气和石油)、核能以及四类可再生能源(太阳能、风能、水能和其他可再生能源,包括生物质能、地热能等)。这个全球近乎实时的电力数据集展示了全球电力系统的动态,包括其小时、日、周和季节性模式,这些模式受到日常周期性活动、周末、季节性周期、常规和非常规事件(如节假日)以及极端事件(如 COVID-19 大流行)的影响。CarbonMonitor-Power 数据集揭示了 COVID-19 大流行在一些国家(如中国和印度)造成了强烈的干扰,导致低碳强度的暂时或长期转变,而在其他一些国家(如澳大利亚)则几乎没有影响。这个数据集为与电力相关的科学研究和政策制定提供了广泛的机会。