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.

大数据正在获得知名度和重要性，其使用在市政当局中获得了更高的影响力。由于这种激增，智慧城市被要求部署架构来管理电动汽车（EV）的能源，并在也称为“消费”的社区中协调生产，消耗和分配来自可再生能源（例如太阳能，风能等）的能源。在智能城市领域，可以使用企业体系结构（EA）来促进市政目标与城市方向之间的相关性，以支持城市中利益相关者的信息技术（IT）。因此，IT与城市目标之间的一致是支持城市服务的持续增长和改善以及能源可持续性的关键过程。然而，尽管针对智能城市中的数据体系结构进行了多项研究，但很少有旨在探索如何在智能城市中应用EA来支持住宅建筑和EV用于市政能源消费的研究。因此，本研究进行了广泛的审查，并开发了可用于智能城市领域的基于大数据管理的体系结构，可用于住宅建筑和电动汽车的能耗。此外，还采用了辅助数据来进行案例研究，以显示发达架构在促进能源消费中的应用。研究结果表明，该架构可提供可互操作的开放式实时，在线和历史数据，以促进能源消耗。分别，