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dc.contributor.authorRuan, Guangchun
dc.contributor.authorWu, Dongqi
dc.contributor.authorZheng, Xiangtian
dc.contributor.authorZhong, Haiwang
dc.contributor.authorKang, Chongqing
dc.contributor.authorDahleh, Munther A
dc.contributor.authorSivaranjani, S.
dc.contributor.authorXie, Le
dc.date.accessioned2020-10-07T17:20:22Z
dc.date.available2020-10-07T17:20:22Z
dc.date.issued2020-09
dc.date.submitted2020-07
dc.identifier.issn2542-4351
dc.identifier.urihttps://hdl.handle.net/1721.1/127832
dc.description.abstractThe novel coronavirus disease (COVID-19) has rapidly spread around the globe in 2020, with the US becoming the epicenter of COVID-19 cases since late March. As the US begins to gradually resume economic activity, it is imperative for policymakers and power system operators to take a scientific approach to understanding and predicting the impact on the electricity sector. Here, we release a first-of-its-kind cross-domain open-access data hub, integrating data from across all existing US wholesale electricity markets with COVID-19 case, weather, mobile device location, and satellite imaging data. Leveraging cross-domain insights from public health and mobility data, we rigorously uncover a significant reduction in electricity consumption that is strongly correlated with the number of COVID-19 cases, degree of social distancing, and level of commercial activity.en_US
dc.publisherElsevier BVen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.joule.2020.08.017en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourcearXiven_US
dc.titleA Cross-Domain Approach to Analyzing the Short-Run Impact of COVID-19 on the US Electricity Sectoren_US
dc.typeArticleen_US
dc.identifier.citationRuan, Guangchun et al. "A Cross-Domain Approach to Analyzing the Short-Run Impact of COVID-19 on the US Electricity Sector." Joule (September 2020): 1-16 © 2020 Elsevier Inc.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Societyen_US
dc.relation.journalJouleen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.date.submission2020-10-07T12:12:47Z
mit.journal.volume4en_US
mit.licensePUBLISHER_CC
mit.metadata.statusComplete


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