Carbon Monitor-Power: near-real-time monitoring of global power generation on hourly to daily scalesBiqing Zhu, Xuanren Song, Zhu Deng, Wenli Zhao, Da Huo, Taochun Sun, Piyu Ke, Duo Cui, Chenxi Lu, Haiwang Zhong, Chaopeng Hong, Jian Qiu, Steven J. Davis, Pierre Gentine, Philippe Ciais and Zhu Liu Abstract: 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. Date: 2022-09 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2209.06086 Access Statistics for this paper More papers in Papers from arXiv.org |
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