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BD4NRG: Big Data for Next Generation Energy

Project description

New reference architecture for smart energy

Advancements in next-generation energy technologies will drastically transform how the world generates and consumes power. Starting with the decentralisation of the energy system, it is necessary to establish a fair and secure engagement between big data and artificial intelligence (AI) technologies. To achieve this, there is a need for more standardisation of big data architectures for smart grids and regulatory frameworks that do not facilitate actual data sharing. The EU-funded BD4NRG project will develop a reference architecture for smart energy to align various architectures together with an interoperable AI-driven big data analytics framework. This will enable cross-stakeholders data-driven services and full interoperability of leading-edge big data technologies with smart grid standards and operational frameworks.

Objective

The 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. There are however some barriers hampering the exploitation of this potential, such as the lack of standardized big data architectures for smart grids and regulatory frameworks not enabling data sharing. In that respect BD4NRG will i) deliver a reference architecture for Smart Energy, which aligns BDVA SRIA, IDSA and FIWARE architectures, SAREF standard and extend COSMAG specification to enable B2B multi-party data exchange, while providing full interoperability of leading-edge big data technologies with smart grid standards and operational frameworks ii) evolve and upscale a number of 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 TRL 7-8 BD4NRG framework iii) deliver a TRL8 open modular big data analytic 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 such framework through the delivery of predictive and prescriptive edge AI-based big data analytics on 13 large scale pilots, deployed by different energy stakeholders (TSOs and DSOs power network operators, aggregators, storage/renewable assets operators, local energy communities, ESCOs, power market operators, municipalities, financial institutions and ENTSO-E), fully covering the energy value chain v) setup a vibrant data-driven ecosystem through the SGBDAA Alliance, which will federate new energy data providers, attract SMEs for novel energy services provisioning through cascading funding and validate a hybrid energy/industry value chain supporting B2B joint digital platforms.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

IA - Innovation action

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Call for proposal

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(opens in new window) H2020-DT-2018-2020

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Coordinator

ENGINEERING - INGEGNERIA INFORMATICA SPA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 833 000,00
Address
PIAZZALE DELL'AGRICOLTURA 24
00144 ROMA
Italy

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Region
Centro (IT) Lazio Roma
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 190 000,00

Participants (37)

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