The BD4NRG Reference Architecture for Big Data Driven Energy Applications

Zenodo (CERN European Organization for Nuclear Research)

Abstract

The rising digitisation of the energy system and related services is unveiling an enormous opportunity for energy stakeholders to leverage on Big Data & AI technologies for improved decision making and coping with challenges emerging from an increasingly complex and interconnected energy system. Initiatives in the field of Big Data Reference Architectures, like IDSA, GAIA-X or FIWARE provide generic frameworks to share, manage and process Big Data. Through alignment among them and integration of missing aspects, an interoperable and secure framework for the energy comes into view. The Reference Architecture presented in this paper moves towards this goal and will be instantiated in a set of concrete use cases within the European Energy Sector. Structurally inspired by SGAM and the BRIDGE Reference Architecture, it puts concrete analytics processes and data source components into context, taking important issues of Data Governance, Security, and Value Creation into account.

Authors 7

1. Katharina Aurelia Wehrmeister Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

2. Efthimios Bothos

   National Technical University of Athens

   Affiliation as printed

   National Technical University of Athens

3. Vangelis Marinakis

   National Technical University of Athens

   Affiliation as printed

   National Technical University of Athens

4. Babis Magoutas

   National Technical University of Athens

   Affiliation as printed

   National Technical University of Athens

5. Alexander Pastor Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

6. Leonardo Carreras Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

7. Antonello Monti Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University