CarbonMonitor-Power near-real-time monitoring of global power generation on hourly to daily scales

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.

本团队构建了一套自2016年1月起高频更新、准实时的全球国家级电力发电量数据集——CarbonMonitor-Power，该数据集覆盖近乎全球范围，时间分辨率为小时至日级。本次发布的数据集采集自全球各洲的37个国家，涵盖8类电力来源：三类化石能源（煤炭、天然气、石油）、核能，以及四类可再生能源（太阳能、风能、水能，以及包括生物质能、地热能等在内的其他可再生能源）。这套准实时全球电力数据集展现了全球电力系统的运行动态，包括其受日常周期性活动、周末、季节周期、常规与非常规事件（如节假日）以及极端事件（如新冠疫情）影响下的小时级、日级、周级与季节级变化规律。CarbonMonitor-Power数据集显示，新冠疫情对部分国家（如中国、印度）造成了显著的电力系统扰动，推动其向低碳强度方向发生短期或长期转型；而对另一些国家（如澳大利亚）的影响则相对有限。本数据集为电力相关的科学研究与政策制定提供了广阔的研究与应用空间。