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Start point
January 2021
11,9
Budget text
Budget: € 11,9 million
(9.9 million from EC)
36
Months

The project


Lead
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.

Idea

Body

Energy System Transformation

  • New energy sources installations lead to growing responsibilities

  • Consumers are now active players. Energy systems are moving from a supplier centric model towards a consumer centric model.

  • The pace of digitization in energy is increasing and consequently the availability of datasets

  • Solutions are required to face heterogeneity, scalability and asynchronicity of the available energy data

  • Energy system management requires big data approach in order to process large volume and varieties of both real and historical data

Approach

Body

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 - BD4NRG Framework, consisting of:

  • Several distributed intelligent collaborative federated nodes, the BD4NRG Data Hubs
  • A graphically enriched Open Modular Big Data Analytics Energy Toolbox
  • A scalable big-data energy analytics environment

BD4NRG will combine DLTs/blockchain technologies with edge processing, Federated Machine Learning and Artificial Intelligence, to operate the data-driven energy ecosystem. Also, the project will make extensive adoption of open sources technology components and tools and Open APIs.

The BD4NRG Framework will include 4 horizontal and 1 vertical (cyber security) layer:

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Data Governance Layer

Title
Data Governance Layer

A necessary middleware to act as a mediator between data users and data providers who may want to decide case by case whether to disclose their data or not. State of the art solutions to guarantee traceability, provenance tracking and accountability but guaranteeing confidentiality as well.

Scalable Big Data Management & Processing Layer

Title
Scalable Big Data Management & Processing Layer

Smart management and processing of data by an intelligent information broker. The content of multiple data sources, being generated, managed and stored in the data management systems and the data hubs of the different operators and actors by innovative components and technology enablers.

Applications Layer

Title
Applications Layer

Analytics-centered applications tailoring power network improved cross-functional decision-making to improve power network reliability, optimize management of flexibility assets, address building-scale energy efficient comfort management and dynamic situated renewable investment risk assessment.

  1. Open Modular Smart Grid Big Data Analytics Toolbox: User-friendly with modern vision of the data analytics Toolbox, providing a working space for self-service capabilities that give autonomy to the end-user combining data that come from different sources.

  2. Data / Models / Resources Marketplace: A virtual workbench with a variety of assets, including data, third party services, machine learning models, computing resources and storage resources as tradable assets providing off-the-shelf tools, library of reusable AI-based machine learning models, external off-domain data sets and reusable data-driven analytics applications.

C

Title
Cyber Security - Data Privacy Layer

A vertical layer to establish user authentication and authorisation to secure the non-open data of the transaction as well as to comply with the EC regulation on Data Protection.

Title
12 Large-Scale Pilots

The overall BD4NRG service analytics reference framework will be applied, implemented, demonstrated and validated in real-life pilots in 12 large-scale demo-sites across 10 countries.

Purpose

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BD4NRG Objectives

Accordion items
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  • To develop a data-driven Reference Architecture for AI-based edge-oriented scalable big data management & analytics in smart energy grids. BD4NRG aims at leveraging, aligning and integrating the existing specifications for data-driven initiatives and underlying B2B Reference Architectures at the interplay among smart energy grids, AI, IoT, Big Data, smart home/building, industry/manufacturing, towards a living reference architecture specifically tailored to the energy value chain. The resulting Reference Architecture will incorporate a set of Open APIs and standardizable interfaces.
  • To develop a semantic and business interoperability framework for cross domain edge-level analytics applications, cross-context learning and datasets spanning entire EPES value chains. BD4NRG will leverage on cross-sectorial IoT and semantic big data interoperability framework for performing structured, federated synchronous/asynchronous machine learning on semantically structured data and data streams at the network edge.

Body
  • To deliver a DLT/blockchain/smart contract -based implementation of an energy data decentralized governance technological enabler. BD4NRG envisions to facilitate and enable seamless open multilateral B2B cross-stakeholder data sharing, trusted data exchange and handling, while allowing full data sovereignty and control of respective data ownership, access, security and protection. Scalability of the planned infrastructure will be achieved through utilizing the blockchain for hash storing.
  • To adapt, evolve, upscale and deploy a technology enabler for advanced edge AI-based big data management, learning and analytics. BD4NRG will provide the necessary capabilities for pushing forward big data management and processing towards the edge, with a view to reduce the major barriers hampering big data & analytics full scale deployment in the smart energy grid domain.
  • To combine and integrate the AI-based technological enablers and data governance stack with the graphical working environment and processing capabilities near-real-time analytics suite and deploy the BD4NRG Open modular Energy Analytics Toolbox. The enhanced learning capabilities together will the edge/IoT edge-level big data management enablers will be combined with a number of capabilities and analytics management open-source commercial suite. The resulting BD4NRG Open modular Energy Analytics Toolbox will hence combine and make them available to end users the advanced ser-friendly graphical working environment capabilities to support custom selection of local and/or third-party assets (via marketplace) including:
    • Discovery of heterogeneous data sources formats
    • A huge variety of analytics ML algorithms/models to be selected
    • A large variety of presentation modalities (reports, charts, etc.)
    • Edge-level available storage and computing resources.
  • To provide an open adaptable tokenized marketplace on the top of Data Governance, Edge AI learning capabilities and edge storage/computing resources incentive-based sharing and access. BD4NRG will adapt, mature and deploy a flexible adaptable Appstore-like marketplace, which will leverage and combine tokenization inspiring principles from value networks and DLT/blockchain and smart contracts to enable the value- and incentive-based mono-commodity and/or multi-commodity sharing and trading of data, AI models/algorithms, edge storage and computing resources.

Body
  • To validate the BD4NRG toolbox and underlying BD4NRG reference framework by developing a variety of near real time edge-level AI-based descriptive, predictive and prescriptive analytics along a number of large -scale field cross-function, cross-stakeholders, cross-domain piloted applications. BD4NRG will deploy, demonstrate and validate from both technical and business perspective, the proposed reference framework and the underlying modular energy analytics toolbox along a 12 of real-life large scale piloted AI edge-based data-driven analytics applications and services.
  • To lay the foundation for pan European smart grid trusted and certifiable data vibrant ecosystem, boosting EU-scale data economy and valorization and impact on standardization. BD4NRG will leverage on the piloted technological achievements and the respective business validation to nurture a high-level durable many-fold impact such as the establishment of the BD4NRG Alliance (Smart Grid Big Data Analytics Alliance - SGBDAA), the strategically activation and continuous enlivening of links with relevant Standardisation bodies, the suitable cascade funding mechanism aimed to support SMEs and start-up through an Open Call with a view to offer innovative data-driven energy services and the cooperation with smart industry/manufacturing with a view to promote a converged smart energy/industry B2B EU-vision and innovation roadmap.