BD4NRG

 

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.

 

Approach

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.

BD4NRG Architecture

The BD4NRG Framework will include four horizontal and one vertical (cyber security) layer:

   

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

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

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.

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.

   

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.

12 large-scale pilots (LSPs) across 10 countries aim to cultivate the shifting towards predictive and prescriptive analytics and to enable multiple data source analytics for a wide range of applications. The large geographical coverage of the pilot sites aims to support the large-scale EU-wide replicability and market take-up of services and solutions in different socio-economical contexts to maximize the impact of BD4NRG services across Europe.

• BD-4-NET Large-Scale Pilots focus on predictive analytics towards forecasting and increasing the efficiency and reliability of the electricity network.
• BD-4-DER Large-Scale Pilots (LSPs) focus on optimizing the management of assets connected to the grid.
• BD-4-ENEF Large Scale Pilots (LSPs) focus on increasing the efficiency and comfort of buildings, and de-risking investments in energy efficiency.

Partners

The project consortium consists of 35 partners from 11 Countries and involves organisations with complementary expertise from the research and industrial area across Europe.

Within the consortium, ACS leads the Task “Pilot planning, requirements and KPIs“, as well as Work Package 2 “System Requirements and Specifications”, which aims to define a Reference Architecture for the BD4NRG System.

 

Acknowledgement

The project has received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under grant agreement no 872613.

 

Announcements

BD4NRG held its second plenary meeting on 26th and 27th October. The two-day assembly was held entirely online, with all 35 project partners attending. The first day, focusing on the 12 Large-Scale Pilots, saw them presenting their use cases as well as their status going into the coming pre-pilot phase. On day 2, the BD4NRG Reference Architecture developed by ACS-led Work Package 2 was presented, followed by discussions on progress and next steps for the technical Work Packages 3, 4 and 5 in particular.