Carbon Monitor-Power: near-real-time monitoring of global power generation on hourly to daily scales

作     者：Zhu, Biqing Song, Xuanren Deng, Zhu Zhao, Wenli Huo, Da Sun, Taochun Ke, Piyu Cui, Duo Lu, Chenxi Zhong, Haiwang Hong, Chaopeng Qiu, Jian Davis, Steven J. Gentine, Pierre Ciais, Philippe Liu, Zhu 

作者机构：Department of Earth System Science Tsinghua University Beijing100084 China Laboratoire des Sciences du Climate et de l'Environnement LSCE Orme de Merisiers Gifsur-Yvette91191 France Product and Solution & Website Business Unit Alibaba Cloud Zhejiang Hangzhou311121 China Department of Earth and Environmental Engineering Columbia University New YorkNY United States Department of Civil & Mineral Engineering University of Toronto TorontoONM5S 1A1 Canada Department of Electrical Engineering The State Key Lab of Control and Simulation of Power Systems and Generation Equipment Institute for National Governance and Global Governance Tsinghua University Beijing China Institute of Environment and Ecology Shenzhen International Graduate School Tsinghua University Shenzhen China Department of Earth System Science University of California Irvine 3232 Croul Hall IrvineCA92697-3100 United States 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2022年

核心收录：

主　　题：Carbon 

摘      要：We constructed a frequently updated, near-real-time global power generation dataset: Carbon Monitor-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 Carbon Monitor-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. © 2022, CC BY.