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  • 标题:Using temperature sensitivity to estimate shiftable electricity demand
  • 本地全文:下载
  • 作者:Michael J. Roberts ; Sisi Zhang ; Eleanor Yuan
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2022
  • 卷号:25
  • 期号:9
  • 页码:1-18
  • DOI:10.1016/j.isci.2022.104940
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryThe growth of intermittent renewable energy and climate change makes it increasingly difficult to manage electricity demand variability. Centralized storage can help but is costly. An alternative is to shift demand. Cooling and heating demands are substantial and can be economically shifted using thermal storage. To estimate what thermal storage, employed at a scale, might due to reshape electricity loads, we pair fine-scale weather data with hourly electricity use to estimate the share of temperature-sensitive demand across 31 regions that span the continental United States. We then show how much variability can be reduced by shifting temperature-sensitive loads, with and without improved transmission between regions. We find that approximately three-quarters of within-day, within-region demand variability can be eliminated by shifting just half of temperature-sensitive demand. The variability-reducing benefits of shifting temperature-sensitive demand complement those gained from the improved interregional transmission, and greatly mitigate the challenge of serving higher peaks under climate change.Graphical abstractDisplay OmittedHighlights•Using thermal storage, HVAC-related energy demand can be shifted in time•We estimate the large-scale potential of such shifts on the U.S. electricity system•HVAC loads are identified by linking hourly electricity demand to fine-scale weather•Shifting half of estimated HVAC demand reduces daily variability by 75 percentEnergy resources; Energy policy; Energy management; Energy Modeling.
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