4.5 Article

Smart city data architecture for energy prosumption in municipalities: concepts, requirements, and future directions

Journal

INTERNATIONAL JOURNAL OF GREEN ENERGY
Volume 17, Issue 13, Pages 827-845

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/15435075.2020.1791878

Keywords

Sustainable energy; energy prosumption; smart cities; big data architecture; electric vehicles; residential energy management

Funding

  1. European Union [824260]
  2. H2020 Societal Challenges Programme [824260] Funding Source: H2020 Societal Challenges Programme

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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.

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