Building and calibrating a country-level detailed global electricity model based on public data

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dc.contributor.author Brinkerink, Maarten
dc.contributor.author Ó Gallachóir, Brian P.
dc.contributor.author Deane, Paul
dc.date.accessioned 2020-12-17T12:35:14Z
dc.date.available 2020-12-17T12:35:14Z
dc.date.issued 2020-12-10
dc.identifier.citation Brinkerink, M., Gallachóir, B. Ó. and Deane, P. (2021) 'Building and Calibrating a Country-Level Detailed Global Electricity Model Based on Public Data', Energy Strategy Reviews, 33, 100592 (12 pp). doi: 10.1016/j.esr.2020.100592 en
dc.identifier.volume 33 en
dc.identifier.startpage 1 en
dc.identifier.endpage 12 en
dc.identifier.issn 2211-467X
dc.identifier.uri http://hdl.handle.net/10468/10840
dc.identifier.doi 10.1016/j.esr.2020.100592 en
dc.description.abstract Deep decarbonization of the global electricity sector is required to meet ambitious climate change targets. This underlines the need for improved models to facilitate an understanding of the global challenges ahead, particularly on the concept of large-scale interconnection of power systems. Developments in recent years regarding availability of open data as well as improvements in hardware and software has stimulated the use of more advanced and detailed electricity system models. In this paper we explain the process of developing a first-of-its-kind reference global electricity system model with over 30,000 individual power plants representing 164 countries spread out over 265 nodes. We describe the steps in the model development, assess the limitations and existing data gaps and we furthermore showcase the robustness of the model by benchmarking calibrated hourly simulation results with historical emission and generation data on a country level. The model can be used to evaluate the operation of today's power systems or can be applied for scenario studies assessing a range of global decarbonization pathways. Comprehensive global power system datasets are provided as part of the model input data, with all data being openly available under the FAIR Guiding Principles for scientific data management and stewardship allowing users to modify or recreate the model in other simulation environments. The software used for this study (PLEXOS) is freely available for academic use. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Elsevier en
dc.relation.uri http://www.sciencedirect.com/science/article/pii/S2211467X20301450
dc.rights © 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) en
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ en
dc.subject Open data en
dc.subject Power system en
dc.subject Power system modelling en
dc.subject Emissions en
dc.subject Global en
dc.title Building and calibrating a country-level detailed global electricity model based on public data en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Maarten Brinkerink, School Of Enginering Office, University College Cork, Cork, Ireland. +353-21-490-3000 Email: maarten.brinkerink@ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2020-12-17T12:17:01Z
dc.description.version Published Version en
dc.internal.rssid 547916599
dc.contributor.funder Energy Exemplar, Australia en
dc.contributor.funder Science Foundation Ireland en
dc.description.status Peer reviewed en
dc.identifier.journaltitle Energy Strategy Reviews en
dc.internal.copyrightchecked Yes
dc.internal.licenseacceptance Yes en
dc.internal.IRISemailaddress b.ogallachoir@ucc.ie en
dc.internal.IRISemailaddress maarten.brinkerink@ucc.ie en
dc.identifier.articleid 100592 en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2302/IE/Marine Renewable Energy Ireland (MaREI) - The SFI Centre for Marine Renewable Energy Research/ en


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© 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) Except where otherwise noted, this item's license is described as © 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
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