The smart grid achieves bidirectional information and energy flow between energy consumer and utility grid, aiding energy users not only to utilize energy, but also to produce, sell, and share energy with other consumers or with the utility grid. This type of energy user is referred to as the “prosumer”. Thus, prosumer management structures are important within the energy market. However, prior studies on energy sustainability have paid little attention to prosumer involvement and management. Likewise, the continuous growth of cities has increased data processing complexity. Consequently, processing and analysis of historical, online, and real-time streaming data from energy sensors and metering devices has become a major issue in smart cities. Therefore, this research aims to present an architecture based on big data to improve energy prosumption in smart community districts by applying enterprise architecture approach grounded on The Open Group Architecture Framework (TOGAF). Accordingly, qualitative methodology is adopted to collect data by employing case study by focus group interview from two energy companies in Norway to preliminarily validate the architecture. Findings from the case studies were demonstrated in ArchiMate modelling language to evaluate the applicability of the architecture. Moreover, findings from this study provide a practical scenario that energy service providers can refer to in designing their own energy data platforms. Essentially, the architecture can be utilized as a guide to help municipalities and policymakers in creating approaches for energy data analytics in smart community districts towards making decisions for future energy prosumption planning.
Authors: Bokolo Anthony Jnr., Sobah Abbas Petersen, Dirk Ahlers, John Krogstie, Klaus Livik