Big Data for Next Generation Energy


BD4NRG envisions to confront big data management challenges for the energy sector, giving a competitive edge to the European stakeholders to improve decision making and at the same time to open new market opportunities. 

BD4NRG aims to enable an incremental decentralized energy data-driven ecosystem and a collaborative data sovereignty driven ecosystem. The goal is to unlock and exploit the economic potential of big data and give to Energy Sector stakeholders, the opportunity to improve their business operational performance. 

To achieve this and to address the emerging challenges in big data management, BD4NRG partners will develop, adapt, deliver and deploy a distributed big data energy analytics framework: the BD4NRG Framework.


  • Delivering a reference architecture for smart energy management. 
  • Offering modular and open TRL8 big data analytics toolbox as a fron-end for the development of analytics services. 
  • Validating this framework through AI-based predictive and prescriptive big data analytics in 13 large-scale pilots. 
  • Establishing a vibrant data-driven ecosystem through the SGBDAA Alliance that will bring together new energy data providers and attract SMEs for the delivery of new energy services.


CARTIF actively participates in the following project actions:

  • Managing pilots related to energy efficiency.
  • Working on analytics related to the improvement of energy certificates and the confidence of the different stakeholders in these certificates.

Expected Results

The main objective is to develop an Open modular Energy Analytics Toolbox that combines and makes available to end-users the advanced user-friendly graphical working environment capabilities to support custom selection of local and/or third-party assets. 




Total Budget: 11,883,025€
Contribution: 9,929,912.50€
Duration: 01/2021-12/2023

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Víctor Serna

Energy Division


Energy efficiency projects:



The main objective of MATRYCS is to define and deploy a Reference Architecture for Buildings Data exchange, management and real-time processing, and to translate this reference architecture into an Open, Cloud-based Data Analytics Toolbox. It will enable AI-based cross-sector analytics for smart energy-efficient buildings, based on seamless data-information-knowledge exchange under respective sovereignty and regulatory principles.

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PROBONO brings together a European multidisciplinary consortium of 47 partners, to turn the six European districts into Green Building Neighbourhoods, with positive energy balance and zero carbon emissions: two large-scale demonstrators and four living labs representing business/owner promoters of the green buildings and neighbourhoods transition.

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frESCO aims to engage with ESCOs and aggregators and enable the deployment of innovative business models on the basis of novel integrated energy service bundles that properly combine and remunerate local flexibility for optimizing local energy performance both in the form of energy efficiency and demand side management.

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The Auto-DAN project aims to enable homes and small businesses across the EU to optimize their energy consumption and provide and assessment of the live energy performance of a building. The solution will focus on the assistive role automation will have in buildings.

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SO WHAT project aims to develop and validate an integrated software for auditing industrial process, planning and simulation of waste heat and cold (WH/C) valorisation systems towards the identification of economically viable scenarios where WH/C and renewable energy sources (RES) cooperate to match local demand.

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