dc.contributor.author | Bokolo, Anthony Junior | |
dc.date.accessioned | 2020-08-24T06:34:57Z | |
dc.date.available | 2020-08-24T06:34:57Z | |
dc.date.created | 2020-08-22T22:37:10Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 1543-5075 | |
dc.identifier.uri | https://hdl.handle.net/11250/2673466 | |
dc.description.abstract | Big data is gaining visibility and importance, and its use is attaining higher levels of influence within
municipalities. Due to this proliferation smart cities are posed to deploy architectures toward managing
energy for Electric Vehicles (EV) and orchestrate the production, consumption, and distributing of energy
from renewable sources such as solar, wind etc. in communities also known as prosumption. In smart city
domain, Enterprise Architecture (EA) can be employed to facilitate alignment between municipality goals
and the direction of the city in relation to Information Technology (IT) that supports stakeholders within
the city. Hence, the alignment between IT and goals of the city is a critical process to support the
continued growth and improvement of city services and energy sustainability. However, despite several
research effort focused on data architecture in smart city, there have been few studies aimed at exploring
how EA can be applied in smart cities to support residential buildings and EV for energy prosumption in
municipalities. Therefore, this study conducts an extensive review and develops an architecture that can
be employed in smart city domain based on big data management for energy prosumption in residential
buildings and EV. Furthermore, secondary data was employed to present a case study to show the
applications of the developed architecture in promoting energy prosumption. Findings suggest that
the architecture provides interoperable open real-time, online, and historical data in facilitating energy
prosumption. Respectively, this study offers exchange of data for sharing energy resources and provides
insights to improve energy prosumption services. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Taylor & Francis | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Smart City Data Architecture for Energy Prosumption in Municipalities: Concepts, Requirements, and Future Directions | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.journal | International Journal of Green Energy | en_US |
dc.identifier.doi | 10.1080/15435075.2020.1791878 | |
dc.identifier.cristin | 1824621 | |
dc.description.localcode | © 2020 The Author(s). Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |