Big data-oriented energy prosumption service in smart community districts: a multi-case study perspective

Abstract

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 energy market. However, prior studies on energy sustainability has paid little attention on 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 was demonstrated in ArchiMate modeling language to evaluate the applicability of the architecture. Moreover, findings from this study provides 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 policy makers in creating approach for energy data analytics in smart community districts towards making decisions for future energy prosumption planning.

Applying Enterprise Architecture for Digital Transformation of Electro Mobility towards Sustainable Transportation

“…But, SGAM is more aligned to energy management in smart grid and less concerned about data integration. Therefore, this study employs Enterprise Architecture (EA) for digital transformation of eMobility services similar to prior study [5,10,15,18] who employed EA for the interaction of EV with the energy grid for interoperability and information flow. EA provides blueprint for the deployment of future systems components to identify gaps for improvement in current systems [18].…”

“…eMobility comprises data and energy communication between EVs, charging station smart grid, etc. [18]. Therefore, DT in eMobility uses a digital interface to manage and source the availability of EV based services which meets the mobility needs of citizens [12].…”

“…EA depicts the fundamental structure of a system and its components, the relationships, environment, and principles governing its design and evolution. It effectively and efficiently communicates and document the essence of IT and business components for stakeholders [18].…”

“…Furthermore, EA aids to plan, lead, design, control, and manage organizations, processes, and/or systems in present, transitionary, and future states, and the relationships among them. It describes an enterprise in terms of its structure, strategy, value streams, information flows, and physical instantiations as well as its transaction, and business models [18]. It also defines the technology, network infrastructure, and utility connections.…”

“…System layer comprise of hardware (physical devices such as metering devices, Internet of Things (IoT) sensors, etc.) [18], IT infrastructures, network infrastructure, and software concerned with real time data processing to support basic connectivity [10], configuration, and integration of the aforementioned components [6,28]. The layer also presents procedures and protocols for data generation and collection between IT components [17].…”