Rising decentralization of the energy system is unveiling an enormous opportunity for energy stakeholders to leverage on big data & AI technologies to improve decision making and prepare the ground for scalable and efficient consumer-centric energy systems, bringing active consumers centre stage. There are however barriers hampering the exploitation of this potential, such as lack of understanding from utilities side on the added value from the availability of increasing data amounts, insufficient culture of data sharing among B2B operators, and utilities with active energy consumers/prosumers, and lack of standardized big data architectures for smart grids and regulatory frameworks not enabling data sharing.
Overall BD4NRG aims at evolving, upscaling and demonstrating an innovative energy-tailored Big Data Analytics Toolbox (BD4NRG Toolbox), significantly contributing to achieve a technoeconomic optimal management of the Electric Power and Energy Systems value chain.
BD4NRG will
i) deliver a Smart Energy Reference Architecture, aligning BDVA SRIA, IDSA and FIWARE architectures, SAREF standard and extend COSMAG specification enabling B2B multi-party data exchange, while providing interoperability of leading-edge big data technologies with smart grid standards and operational frameworks
ii) deploy TRL 5-6 technology enablers, such as scalable sovereignty-preserving hybrid DLT/off-chain data governance, big data elastic pipeline orchestration, IoT/edge AI-based federated learning and multi-resource sharing tokenized marketplace, loosely integrate and deploy them within the BD4NRG framework
iii) deliver a TRL8 open modular big data analytics toolbox as front-end for one-stop-shop analytics services development by orchestrating legacy and/or third party assets (data, computing resources, models, algorithms)
iv) validate its framework, by delivering predictive and prescriptive AI-based big data analytics on 12 large scale pilots, deployed by different energy stakeholders (TSOs, DSOs, aggregators, storage/renewable assets operators, energy communities, ESCOs, municipalities, financial institutions), fully covering the energy value chain
v) setup a data-driven ecosystem in which new energy data providers will be federated, attract SMEs for novel energy services provisioning through cascading funding and validate a hybrid energy/industry value chain supporting B2B joint digital platforms
