Energy Data Space policy paper : ETIP SNET, European Technology and Innovation Platform Smart Networks for Energy Transition.
Date: 2023-12-21
Institutions: Directorate-General for Energy
Subjects: EU energy policy, electrical energy, energy market, energy research, energy transition, renewable energy

Energy Data Space 

Policy Paper  

ETIP SNET 

European  Technology  and  Innovation 

Platform  Smart  Networks  for  Energy 

Transition 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Energy Data Space 

Authors 
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Antonello Monti (RWTH Aachen University and Fraunhofer FIT) 
Laurent Schmitt (Digital4Grids) 
Alberto Dognini (RWTH Aachen University and Fraunhofer FIT) 
Ricardo Bessa (INESC TEC) 
Elena Boskov-Kovacs (Blueprint Energy) 
Georg Hartner (Entarc.eu/ FH Oberösterreich) 
Tasos Tsitsanis (Suite5 Data Intelligence Solutions) 
Stamatis Diakakis (UBITECH Energy) 
Santiago Gallego Amores (Iberdrola) 
Carlos Damas Silva (E-REDES) 
Natalie Samovich (Enercoutim) 

Editors 
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• 
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Antonello Monti (RWTH Aachen University and Fraunhofer FIT) 
Laurent Schmitt (Digital4Grids) 
Alberto Dognini (RWTH Aachen University and Fraunhofer FIT) 

Support to the publication of this Paper 
• 
Giada Bertolini (Zabala Innovation) 
•  Maria Laura Trifiletti (Zabala Innovation) 
•  Martin Bracken (CLERENS) 
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Edoardo Genova (Zabala Innovation) 

Acknowledgements 
This work has been performed with the contributions provided by the six projects of the energy data spaces cluster and their coordinators: the 
Coordination and Support Action (CSA) int:net as well as the five Innovation Actions (IA) belonging to the Horizon-Europe call “Establish the 
grounds for a common European energy data space”, namely ENERSHARE, OMEGA-X, DATA CELLAR, SYNERGIES, and EDDIE. 

EUROPEAN COMMISSION 

Directorate-General for Energy 
Directorate B – Just Transition, Consumers, Energy Efficiency and 
Innovation Unit B5 – Innovation, Research, Digitalisation, 
Competitiveness 

Contact: Mugurel-George Păunescu 

E-mail: mugurel-george.paunescu@ec.europa.eu 

European 
Commission 
B-1049 
Brussels 

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Energy Data Space 

Energy Data Space 

Policy Paper 

ETIP SNET 

2023 

Directorate-General for Energy 

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Energy Data Space 

LEGAL NOTICE 

This document has been prepared for the European Commission however it reflects the views only of the authors, and the European Commission is not 

liable  for  any  consequence  stemming  from  the  reuse  of  this  publication.  More  information  on  the  European  Union  is  available  on  the  Internet 
(http://www.europa.eu). 

PDF 

ISBN 978-92-68-10945-8 

doi: 10.2833/586947 

MJ-05-23-561-EN-N 

Manuscript completed in November 2023 

This document should not be considered as representative of the European Commission’s official position. 

Luxembourg: Publications Office of the European Union, 2023 

© European Union, 2023 

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For any use or reproduction of elements that are not owned by the European Union, permission may need to be sought directly from the respective 
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2023

Directorate-General for Energy 

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Energy Data Space 

CONTENTS 

CONTENTS ...................................................................................................................................................................... 5 

INDEX OF FIGURES ...................................................................................................................................................... 6 

EXECUTIVE SUMMARY ................................................................................................................................................ 7 

1. Introduction ............................................................................................................................................................. 8 

1.1  Introduction and scope of the document ....................................................................................................................................................................................... 8 

1.2  Short introduction to data spaces ..................................................................................................................................................................................................... 8 

1.3  Data management strategies .............................................................................................................................................................................................................. 9 

2. Reference architecture for Energy Data Spaces..................................................................................... 10 

2.1  GAIA-X ............................................................................................................................................................................................................................................................ 10 

2.2  BRIDGE Data Management Architecture ..................................................................................................................................................................................... 11 

3. Data spaces in the transforming energy systems ................................................................................. 12 

4. Exemplary use-cases in the energy sector ............................................................................................... 13 

5. Reference data flows ........................................................................................................................................ 15 

6. Key challenges implementing Energy Data Spaces in Europe ........................................................... 16 

7. Policy and regulation recommendation ...................................................................................................... 19 

References .................................................................................................................................................................. 22 

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Energy Data Space 

INDEX OF FIGURES 

Figure 1 - High-level overview of the GAIA-X architecture showing the major architecture elements and functions accompanied 
by the Federation Services .................................................................................................................................................................................................................... 10 

Figure 2 - DERA 3.0 layered architecture. .................................................................................................................................................................................... 11 

Figure 3. IEC TC57 Working Group 21: Grid – behind the meter data interactions. .............................................................................................. 15 

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Energy Data Space 

EXECUTIVE SUMMARY 

A reliable and secure common European data space for energy is a key element of the system digitalisation, as stated in the EU action 
plan “Digitalising the energy system” and in the European Data Act, allowing to enhance the integration of renewable energy sources 
and hence advancing towards the goals set by the ‘Fit for 55’ package and the RePower plan. 
This policy paper describes the state of data spaces in the energy system, depicting the background as well as the domain applications, 
and the necessary steps to comprehensively leverage such technical solution at a large scale. 
At the domain-agnostic level, a data space is defined as a framework that enables the data sharing in an ecosystem, subject to precise 
rules concerning security, legal compliance, and remuneration; each data space is systematically built with specifications, to be iteratively 
updated,  on  business,  legal,  operation,  functional,  and  technology  categories.  In  the  energy  domain,  the  development of a  European 
framework for data sharing needs to consider the various strategies of data management across the member states; particularly, the 
data exchange among market participants can be carried out according to three alternative models: decentralized, centralized and hybrid. 
Consequently, the design of a common European energy data space must account for the harmonization and interoperability of the 
various national initiatives and models. 

Moreover, the new challenges introduced by the data spaces lead to the use of reference architectures to address commonalities and 
align  different  solutions.  Among  the  existing  reference  architectures,  GAIA-X  provides  a  cross-domain  structure  divided  into  the 
infrastructure  ecosystem  and  data  ecosystem,  whereas  the  BRIDGE  DERA  3.0  starts  from  the  SGAM  model  to  depict  the  necessary 
building blocks for the local and federated data spaces. 
The current and upcoming transformations in the energy systems fit with the functionalities enabled by the data spaces, enhancing the 
overall power management. Particularly, the transformations are directed to the following groups: (i) the  control room for system 
operator, in which the data spaces foster the TSO-DSO communication and the control of DER, (ii) the grid flexibility, requiring new 
market mechanisms to manage intraday wholesale transactions, (iii) the role of buildings in flexibility, enhancing the accessibility to 
“behind the meter” data and the exchanges with the Flexibility Service Providers (FSP) to improve the congestion management, (iv) the 
residential  energy  optimization  &  smart  charging,  in  which data  spaces allow  the  prosumers  (as  DER owners)  to  interact  with 
various flexibility markets, and (v) the operation of the energy system across different sectors, such as electricity, gas, heating, 
cooling, transport, and industry. 

Starting from these transformations specific use cases, centrally based on data spaces, have been defined and described; this definition 
considered the existing regulatory requirements, the technological availability, and the relevance for industry or societal challenges. The 
use cases presented in this document include, among others, the optimization of transmission and distribution systems operations, the 
instantiation and operation of energy communities, and the inter-borders EV services. Each use case depicts a precise situation in which 
data sharing allows, on one hand, to generate value without necessarily exchanging the data itself and, on the other hand, to foster 
optimization via data-enabled analytics solutions. 
The systematic deployment of energy data spaces requires to address several key challenges, which are discussed in this document. 
Technical challenges include the accessibility of data (from smart meters and DER devices), the role of identity management component, 
and the harmonization of data models and components. These challenges are strictly related to the need of create the conditions for a 
wider customer involvement. Data spaces are in this respect a great opportunity to make clear the central role of the customers in terms 
of data provisions. 

In  general,  regulatory  and technical  challenges  have  to  be  addressed  together,  to  avoid  further late  issues.  From  the organizational 
viewpoint, the measures to federate different initiatives in the ecosystem and its long-term maintenance have a foremost importance. 
It is vital to obtain from the beginning an easy interoperability process and to avoid any possibility of data silos. The current situation is 
vice versa conditioned by several closed solutions that make the involvement of customers and customers assets quite difficult.  
Another relevant challenge corresponds to the entire re-thinking of business processes, in the whole energy sector. In fact, data spaces 
design must consider the evolution of traditional market roles towards a new decentralized digital energy infrastructure, whose grid 
control balancing is centrally supported by sector coupling and end-consumers. It is a unique opportunity in this respect to achieve a 
higher level of democratization making sure customers have the right conditions to participate to the system. 
Starting  from  the  identified  challenges,  policy  and  regulation  recommendations  have  been  derived.  Cooperation  among  different 
European initiatives is fundamental and thus regulations for the interoperability of local and flexibility energy markets must be made 
effective, while implementing measures for the data protection and privacy. Rules for interoperability and, at the same time, opening of 
the data silos should be strictly enforced to make sure that devices can be seamlessly integrated in the energy system bringing also 
significant advantages not only to the customers but also to the grid operators that would have easier access to flexibility. 
Concerning the investments and infrastructures, considerable resources shall address the hardware infrastructures as well as programs 
to ensure the participation of end users, fostering the full uptake of energy data spaces. 

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Energy Data Space 

1. Introduction 

1.1 Introduction and scope of the document 

Energy data spaces are one of the key pillars of the recently published “Digitalization of Energy Action Plan” released by the European 
Commission (EC) during the Fall 20221 as well as the new European Data Act recently finalized2. They constitute a necessity to enable a 
digitalized energy system with more available data streaming from all energy-related sectors that can be shared among trusted parties. 
A common European energy data space aims to strengthen interoperability among different systems and make it possible for more 
innovative services to enter the market.  

The  topic  has  been  already  quite  actively  investigated  and  it  is  also  at  the  center  of  a  cluster  of  projects  funded  by  the  European 
Commission. These projects, being Innovation Actions, have a medium-long range perspective so that we can expect to see results in the 
market in the next 5 years. Nevertheless, previous work in this field, as also summarized by the Coordination and Support Action (CSA) 
OpenDEI3, makes possible to foresee applications also for a shorter term. 
Goal of this policy paper is to give a short technical introduction to the topic, providing references for a deeper analysis, and then to 
focus on  the  identified  opportunities,  challenges  and  necessary  actions  for  a  quick  deployment  of  a common European  energy  data 
space.  For  this  reason,  the  document  is  as  much  as  possible  technology  agnostic  and  focuses  on  the  next  steps  for  the  concrete 
implementations. 

Goal of this policy paper is to give a short technical introduction to the topic, providing references for a deeper analysis, 
and then to focus on the identified opportunities, challenges and necessary actions for a quick deployment of a common 
European energy data space. For this reason, the document is as much as possible technology agnostic and focuses on 
the next steps for the concrete implementations. 

Energy data spaces necessitate the use of advanced technologies and robust connectivity, in conjunction with an optimized transportation 
infrastructure, to establish a secure “Internet of Energy”4. The Internet of Energy, whose deployment has the data spaces as fundamental 
pillar,  pertains  to  interconnected  energy  systems  that  leverage  digital  technologies  to  optimize  energy  production,  distribution,  and 
consumption. Likewise,  the  optimized  transportation  system  utilizes  digital  technologies  to  enhance  transportation  efficiency,  reduce 
carbon emissions, and promote sustainable modes of transport. 

1.2 Short introduction to data spaces 

In 2020, the European Commission’s policy titled “A European strategy for data” introduces the concept of a “data space”, aiming to 
protect data generated by European people and enterprises, while at the same time keeping it open for innovative uses. In this view, 
the data should foster Europe's digital single market and, meanwhile, address the “societal challenges”, which in the energy domain 
include easing the energy transition to carbon-free according to Green Deal and future Electricity Market Design targets. 

A data space, as defined by the Data Spaces Support Centre (DSSC) project,5 is a framework that supports data sharing within a data 
ecosystem. It is constituted by a clear structure in which the participants collaborate on data assets; in particular, they agree to trade 
and share data in a way that is compliant with the agreed data values and relevant regulations as well as ensuring fair treatment for 
all parties involved. From the business perspective, the trusted and secure sharing of commercial data assets is enabled, following 
automated controls on legal compliance and remuneration. 

From a domain-agnostic perspective, each data space deployment is characterized with respect to the following five categories: 

• 

• 

Business: the business model around the data exchange (e.g., the consumption data to deploy flexibility planning in the 
wholesale market) and the business roles of parties. 
Legal: the legal framework includes (a) the cross-cutting legal frameworks, (b) the organizational aspects and (c) the 
contractual instruments. 

•  Operation: including information on operational framework (use cases), the processes and activities. 

1Digitalising the energy system - EU action plan - COM/2022/552 final. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52022DC0552. 
2 European Data Act. https://digital-strategy.ec.europa.eu/en/library/data-act-proposal-regulation-harmonised-rules-fair-access-and-use-data 
3 OPEN DEI - https://www.opendei.eu 
4 Internet of Energy – Connecting Energy Anywhere Anytime - https://doi.org/10.1007/978-3-642-21381-6_4. 
5 Data Spaces Support Centre - https://dssc.eu/. 

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Energy Data Space 

• 

• 

Functional: described according to the technical and governance building blocks, which are deployed according to the 
required technical services (and their dependencies) as well as the data standards. 
Technology: with specifications on the adopted standards, references or the required software components. A major 
goal is to ensure interoperability among inner parties and with other data spaces. 

Additionally, the following features have to be pursued: 

• 
Security and Privacy: focusing on ensuring the security and privacy of the data exchanged within the data space. 
•  Quality and Integrity: pertaining to the quality and integrity of the data within the data space. It includes aspects linked 

• 

with metadata such as data validation, data cleansing, data accuracy, data consistency. 
Governance and Policy:  encompassing the  governance  structure  and  policies  governing  the  data  spaces,  addressing 
decision-making, data governance frameworks (including rules and practices for management and operations), policies 
for data sharing and access, energy-related policies and regulations. The term “governance body” is used to refer to 
the role of a specific partner (or set of partners) in the data space initiative, which bears the responsibility for creating 
and maintaining the governance framework. 

The achievement of energy domain transformation depends on the re-shape of complex energy flows, involving different sectors 
(like consumers, mobility, buildings, retailers, flexibility service providers, grid operation and manufacturing) and relying on the 
digitalized data exchange to be managed efficiently and in real-time. This digitalized data exchange facilitates an energy system 
which can accelerate, automate, plan, and anticipate processes far better than at present. Hence, the development of an energy 
data space cannot be delivered as a single platform but must be built incrementally, meaning that applications and systems 
must be capable of interoperating and exchanging data across different data spaces. Even more, existing national Data Spaces 
must be integrated in a federated way. 

1.3 Data management strategies 

To  establish  an  effective  European  framework  for  sharing  energy  data,  it  makes  sense  to  reflect,  how  data  management  is 
approached  today.  Two  very  important  sources  on  this  are  the  TSO-DSO  Data  Management  Report6  and  the  GEODE  Data 
Management Fact Sheet.7  Especially the latter dives into the fact that following Article 23 of Directive (EU) 2019/944 leaves the 
approach to data management for energy services to Member States, empowering them to tackle European legal requirements 
according to their subsidiary needs. That freedom, in fact, leads to three main architectural approaches that we find in many 
member states, often in parallel for different types of relevant data:  

• 

• 

• 

In the decentralized model, data stays where it is captured (e.g., metering information at DSO, contract information 
at supplier, capability data at Distributed Energy Resources (DER), etc.). Market actors are working together to develop 
standardized market communication and exchange data either based on explicit consent of the data subject or under 
the umbrella of clearly defined business processes. Examples are given by frameworks in Austria (EDA), German market 
communication and France.  

The centralized model includes a data hub to which data is sent and stored. All business processes run on 
that hub and results are sent back to its clients. It is operated and developed by a specific party or service 
provider.  Market  participants  use  its  functionalities.  This  approach  is  deployed,  for  example,  in  Finland  and 
Estonia. 

The  hybrid  model  is  a  combination  of  the  two  previous  models.  All  market  participants  can  communicate  in  a 
decentralized manner, but in some use cases (e.g., compliance monitoring or brokering access to data), there are task-
specific central structures. An example, pertaining the smart meter context, is Spain, where data stays with the DSO as 
the  “metered  data  administrator”,  and  access  for  final  customers  and  third  parties  is  brokered  by  AELEC-operated 
DataDis8. 

The examples above show just the context of meter data access, yet the classification is also observed for the management of 
other  data.  For  example,  we  see  decentralized,  centralized  and  hybrid  management  and  sharing  organization  for  flexibility 
registers,  connection  point  registers,  flexibility  service  provider  master  data  or  facilitation  of  Energy  Communities  and  other 
collective self-consumption schemas.

6 https://www.entsoe.eu/2016/07/27/tso-dso-data-management-report/. 
7 https://www.geode-eu.org/wp-content/uploads/2020/05/202005-Fact-sheet-GEODE-Data-Management-FINAL.pdf. 
8 DATADIS - https://aelec.es/datadis/ 

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2. Reference architecture for Energy Data Spaces 

The digitalization of European energy systems introduces new challenges in terms of data, knowledge, and technology adoption due to 
critical interoperability challenges for the underlying digital platforms. These challenges are emphasized in the deployment of energy 
data spaces and are addressed, consequently, by the developed reference architectures, defined as model for building architectures that 
exhibit known commonalities.9 The following section introduces existing prominent examples for data space architectures. However, it is 
noteworthy  that  regulatory  and  legal  developments  enable  a  healthy  competition  and  a  strive  for  innovation  between  data  space 
technologies. Overall, it is therefore crucial to ensure minimal alignment and interoperability of these reference architecture options. 

2.1 GAIA-X 

One reference at European level is constituted by GAIA-X. Its architecture, shown in Figure 1, employs digital processes and information 
technology, aiming to facilitate the interconnection between all participants in the European digital economy.10 

The whole GAIA-X ecosystem, represented in the architecture, is structured into (i) a data ecosystem and (ii) the infrastructure ecosystem. 
Activity in the infrastructure ecosystem is focused on providing or consuming infrastructure services, whereas in data ecosystems the 
main asset is given by the data model and data information. 

Figure 1 - High-level overview of the GAIA-X architecture showing the major architecture elements and functions accompanied by 
the Federation Services 

9 OPEN DEI - Reference Architectures and Interoperability in Digital Platforms https://www.opendei.eu/wp-content/uploads/2022/10/REFERENCE-
ARCHITECTURES-AND-INTEROPERABILITY-IN-DIGITAL-PLATFORMS.pdf. 
10 GAIA-X Technical Architecture https://www.data-infrastructure.eu/GAIAX/Redaktion/EN/Publications/gaia-x-technical-
architecture.pdf?__blob=publicationFile&v=5. 

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2.2 BRIDGE Data Management Architecture 

The BRIDGE Data Management Working Group focused on the further enhancement of Data Exchange Reference Architecture 
(DERA), iterating to version 3.0.11 The architecture starts from the Smart Grid Architecture Model (SGAM) and associated CIM data 
exchanges to integrate data spaces in each interoperability layer: component, communication, information, function and business. 
The DERA 3.0 architecture is represented in Figure 2. An important aspect of the model is the differentiation between “local data 
space” and “federated data space”, highlighting the building blocks, at the different interoperability layer, for each configuration. 
The BRIDGE architecture is aligned with the Harmonised Electricity Market Role Model (HEMRM)12 and so offer easy instantiation 
options in the electricity sector in particular. 

Figure 2 - DERA 3.0 layered architecture. 

Beyond the energy domain, data spaces initiatives in other sectors have achieved advanced and tangible results; together with 
the “Industry 4.0” in the manufacturing domain, one example is given by CATENA-X13 in the automotive domain. In general, in 
regard to the data exchange, the energy domain shall consider also other areas of activity,  analysing the best practices and 
integrate them in the upcoming deployments. 
Similarly in Tourism DATES14 project activated cross domain stakeholders within tourism sector actors focusing on resilience use 
cases, low probability high impacts events management and other climate adaptation related use case. BD4NRG15 and DATES 
projects conducted a joint workshop to explore interfaces, cross leverage between tourism and energy domains impacting data 
spaces design.  
Leveraging the best practices from these parallel domain experiences can enable the integration of energy data with other data 
domains,  such  as  mobility,  industry,  environment,  tourism  and  agriculture.  Development  of  new  cross-sectoral  services  and 
applications, including marketplaces16 can improve overall system performance, user experiences, and social impact of the system 
of system approach. 

11 BRIDGE Data Management https://bridge-smart-grid-storage-systems-digital-projects.ec.europa.eu/working-groups/data-management. 
12 The Harmonised Electricity Market Role Model (HEMRM), ENTSO-E, EFET and EBIX, version 2022-01. https://eepublicdownloads.entsoe.eu/clean-
documents/EDI/Library/HRM/Harmonised_Role_Model_2022-01.pdf 
13 Catena-X https://catena-x.net/en/ 
14 DATES https://www.tourismdataspace-csa.eu 
15 BD4NRG https://www.bd4nrg.eu/toolbox 
16 https://aioti.eu/wp-content/uploads/2021/03/Open-Energy-Marketplaces-Evolution-Published.pdf 

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3. Data spaces in the transforming energy systems 

Data spaces provide the technology to address the current and upcoming transformations that are involving the energy systems, 
fostering  the  opportunities  and  enhancing  the  operations  optimization  towards  the  achievement  of  climate  neutrality  goals. 
Particularly, five aspects of energy systems transformation, to be interconnected with data spaces deployment, are presented 
hereafter. 

1.  Control room for system operator 

This category of use cases is related to the progressive evolution of grid control room environments to adapt to new regulatory 
developments and the future electricity market design as well as the accelerated deployment of distributed energy resources, as 
the  result  of  the  increased  system  electrification.  In  fact,  the  ongoing  exponential  deployment  of  flexible  assets,  located  in 
consumer premises, is creating new dynamic flow patterns in DSO networks as well as new cross border flow coordination across 
TSOs and DSO boundaries. 
The  first  set  of data  space,  largely  based  on  the  Common  Information  Model  (CIM)  and  digital  twins  concept,  should  enable 
streaming of real-time structured information across grid control room environments down to DER interfaces. 

2.  Grid flexibility 

The second category is related to the development of new market mechanisms to manage intraday wholesale transactions, grid 
ancillary services and congestion management, leveraging DER flexibility to optimize grid operation. In this regard, the typical 
service taxonomy to be considered for the development of these data spaces has been well summarized through the OneNet17 
project. 
The associated data space should support the next implementation of distributed flexibility registers across European TSO and 
DSO to ensure necessary coordination for grid ancillary services and congestion management through single sets of interoperable 
APIs. Moreover, all associated data exchanges should be secured and ensure consent based and interoperable data exchanges 
as per the new data act. 

3.  Role of buildings in flexibility  

Buildings play a central role in achieving the climate neutrality goals. Given the lifespan of buildings this means that a building’s 
CO2 contribution is primarily from its energy performance, and several surveys demonstrate it needs to be improved significantly. 
Hence the crucial importance to progress from qualitative to data driven quantitative building energy performance assessments 
leveraging smart metering devices together with dedicated measurement devices associated to “behind the meter” Demand-Side 
Flexibility (DSF).  

At the “grid-edge”, the accelerated growth in the electrification of transport and heating significantly increases the need for grid 
reinforcements  as  well  as  add  new  renewable  transient  congestions  to  be  managed  through  new  flexible  connections  and 
flexibility markets. Moving forward the ability to dynamically balance the local LV distribution systems will soon become critical 
to optimize grid available capacity; hence, buildings represent critical energy hubs to mitigate congestion risks and turn intraday 
volatility into new revenue opportunities to consumers. High level real-time monitoring requirements will need to be managed by 
service providers, whilst provision of local services needs to be coordinated and potentially constrained by system operators, in 
order  not  to  violate  grid  limitations.  Submetering  and  Dedicated  Measurement  Devices  will  be  integrated  into  the  European 
regulatory  framework,  allowing  multiple  Flexibility  Service  Providers  (FSP)  and  multiple  suppliers  to  operate  behind  a  final 
customer’s connection. 

4.  Residential energy optimization & Smart Charging  

DER  such  as  residential  PV,  storage,  Electrical  Vehicle  (EV)  bidirectional  charging  or  heat  pumps  are  expected  to  deploy 
exponentially through consumer residential environments. These DERs are predominantly owned by prosumers who are implicitly 
opting for new cloud connection offered by the Original Equipment Manufacturer (OEM) of the DER to manage associated remote 
operation  and  maintenance.  While  most  of  these  connected  services  are  today  focusing  on  basic  energy  management  and 
maintenance  services,  new  optimization  opportunities  arise,  introducing  new  real-time  connectivity  challenges  between  DER 
owners,  DER  operators  and  new  energy  service  providers  (whether  aggregators  or  energy  communities).  This  new  approach 
requires to develop new prosumer DER data spaces.  

Furthermore, associated market enrolment mechanisms should be automated and made simple to ensure a fluid customer opt-
in/opt-out for their preferred energy service provider and so ensure plug and play interactions with the various flexibility markets. 
A key principle for the design of this data space is that the participation of DER flexibility into flexibility markets must remain a 
matter of choice of DER owners, meaning consumers should be able to dynamically opt in/out for such services or decide for 

17 OneNet - One Network for Europe https://onenet-project.eu/. 

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Energy Data Space 

most attractive FSP offerings through their user experience. New integration strategies and APIs for mass produced residential 
DERs need to be developed through the flexibility code to ensure a level playing participating of all resources into the market. 

5.  Smart sector integration 

Data spaces can play pivotal role in enabling smart sector integration in energy18, which is the coordinated planning and operation 
of the energy system across different sectors, such as electricity, gas, heating, cooling, transport, and industry. Data spaces in 
energy can facilitate the exchange and sharing of data among heterogeneous  energy actors, such as consumers, prosumers, 
aggregators,  utilities,  grid  operators,  regulators,  and  service  providers,  while  supporting  the  development  and  deployment  of 
innovative  data-driven  solutions  and  services  that  can  enhance  the  efficiency,  flexibility,  reliability,  and  sustainability  of  the 
overall energy system. 

Regarding the integration facilitation, data spaces can enable the coupling of different energy carriers, such as electricity, green 
hydrogen, heat, through power-to-X technologies, such as power-to-gas, power-to-hydrogen, and power-to-heat. Data exchange 
and interoperability among these technologies and the respective energy networks would allow for the optimal use of renewable 
electricity and the reduction of greenhouse gas emissions as well as faster and more efficient integration and capacity building. 

These five aspects are fully aligned with the 9 High-Level Use-Cases (HLUCs) from the ETIP SNET Roadmap 2022-203119, which 
describes  the  details  of  the  most  urgent  R&I  needs  to  be  tackled  through  European  Commission  and  national  R&I  work 
programmes and calls. Among the 9 HLUCs, the data spaces adoption will have the strongest impacts in the HLUC 2 (Market-
driven TSO–DSO–System User interactions), HLUC 3 (Pan European Wholesale Markets, Regional and Local Markets), HLUC 5 (One 
stop shop and Digital Technologies for market participation of consumers (citizens) at the center) and HLUC 9 (Flexibility provision 
by Building, Districts and Industrial Processes). 

4. Exemplary use-cases in the energy sector 

The concept of an energy data space brings forth the potential for new or enhanced use cases (UCs) for different stakeholders, 
namely consumers, local communities, TSOs, DSOs, multi-energy utilities, RES investors and operators, and non-energy service 
providers. However, a fundamental prerequisite to fully capitalize on the benefits of the data space is to design UCs that: a) 
explore and combine data from different owners (i.e., cross-silo data sharing), and/or b) exchange/transfer data-driven models 
and knowledge extracted from shared data. 

To ensure the realism of the proposed UCs, it is crucial that the solutions align with widely accepted and implemented regulations, 
while identifying gaps in the current policy preventing the use case to be implemented with more success across the European 
Union (EU). Additionally, the technology required for implementation should be readily available, and the proposed solutions must 
address actual industry or societal problems. To assess these aspects, each UC was evaluated based on the following criteria: 

• 

• 

• 

Alignment  with  social,  political,  and  regulatory  requirements.  The  level  of  compatibility  between  the  UC's 
requirements and existing EU regulations will be assessed to determine the potential conflicts. 

Technological  requirements  and  availability.  The  necessary  technologies  for  implementing  the  UC  and  their 
availability in the market will be evaluated to ensure feasibility. 

Importance and real-world need. The significance of the proposed solution and its practical relevance in addressing 
industry or societal challenges will be assessed. 

Below, a non-exhaustive list of use cases from the energy sector that take full benefit from a data space is presented. 

• 

Transmission and distribution system operation. TSO and DSO can improve the predictability of load and renewable 
energy forecasting by using the data space to promote close to real-time data sharing of individual or aggregated data 
from RES producers, DER operators, consumers, aggregators, etc.; a marketplace for forecasting is one potential use case 
[Gonçalves et al., 2021]. Another use case is to track behind-the-meter small-scale DER growth , flexibility potential, as well 
as real-time performance when participating in flexibility markets and this augmented observability can be used to better 
plan  the  network  and  system  considering  technology  diffusion  forecasts  [Heymann  et  al.,  2021],  e.g.,  identify  attractive 
network areas for the installation of flexible DER. Real-time data shared by consumers can be also used for outage detection 
and location as well as near real-time congestion mitigations and emergency smart load shedding controls , potentially 
combined with data from other sectors such as ICT service providers. 

• 

Electricity monitoring and local self-consumption optimisation bring benefits to households and SMEs since it has 
enormous potential to save energy, reduce energy bills as well as stack new revenue opportunities from flexibility. It supports 

18 Smart Sector Integration, towards an EU System of Systems - https://smart-networks-energy-
transition.ec.europa.eu/sites/default/files/publications/ETIP-SNET-PP-Sector-Coupling-towards-an-EU-System-of-Systems-.pdf 
19 ETIP SNET R&I implementation plan 2025+ https://op.europa.eu/en/publication-detail/-/publication/1f335dcf-461d-11ee-92e3-01aa75ed71a1 

13 

 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
Energy Data Space 

the active implicit customers participation in flexible mechanisms which can be leveraged by system operators to manage 
electricity network congestion and stability more efficiently. Future data exchange platforms will allow electricity consumers 
to  consult,  in  an  integrated  manner  and  through  single  interfaces,  all  disaggregated  information,  current  and  historical, 
related to their boundary meter and corresponding dedicated measurements devices. Users should be able to authorize 
third parties service providers (e.g., aggregators) to access their data and thus offer them relevant energy services. Such 
platforms  should  also  integrate  other  DER  use  cases,  such  as  smart  and  bidirectional  charging  of  electric  vehicles,  the 
participation in energy communities as well as the monitoring of heat pump operation. 

•  Data centers energy control. This UC focuses on addressing the challenges posed by the rapid growth of data centers in 
Europe.  The  development  of  a  digitalized  control  infrastructure,  in  the  form  of  a  digital  platform,  will  enable  flexible 
coordination  of cooling storage and  waste  heat  reuse  in  data  centers.  The control  and  scheduling  implemented  at  data 
center sites will utilize real-time energy and market data, including energy consumption, demand, and electricity prices, to 
optimize the operation of data centers and regulate server room temperatures, thereby reducing carbon emissions. 

• 

• 

Inter-borders EV services. The challenges related to roaming of mobility services (i.e., EV charging) across borders. The 
main obstacles include the lack of a legislative framework, poor information about the location and availability of public 
charging  stations  across  borders,  absence  of  real-time  information  about  availability,  tariffs  and  session  prices,  non-
compatible tools and apps for accessing charging stations, and non-transparent business models with complex value chains. 
To  overcome  these  obstacles,  standardization  and  interoperability  of  the  charging  infrastructure,  particularly  the 
communication protocols, are proposed as solutions. 

Instantiation of Local Energy Communities (LEC) and simulation of business models. Optimize, in a planning phase, 
the sizing of LEC (i.e., DER capacity) and simulate their operation (e.g., estimate an internal reference price to study different 
business models) by combining data from different consumers. The data shared by different data owners (e.g., consumers, 
original equipment manufacturer - OEM, RES producers) is crucial to compute the benefits of belonging to the community.  

•  Operation of LEC. On top of “standard” functions like peer-to-peer trading, data shared between the community members 
can  be  used  to  compute  additional  sustainability  indicators,  such  as  the  traceability  of  green  energy  supply  within  the 
community or “happy hours” for EV charging. Moreover, this data sharing fosters the development of local circular economic 
business models, which are particularly appealing in agricultural settings characterized by seasonal activity. In these models, 
a surplus of RES can be exchanged for other products/services through barter exchanges, including water, PV panels cleaning, 
raw materials, and biofuels. 

•  Demand-Response schemes for final prosumers. This UC exploits data spaces to revolutionize the energy sector by 
transforming demand-response schemes through seamless data sharing and real-time communication between consumers 
and  grid  operators.  Via  data  spaces  in  the  energy  sector,  consumers  are  also  enabled  to  engage  in  demand-response 
programs, optimizing energy consumption through real-time analysis. Grid efficient management is empowered, reducing 
strain, and incentivizing consumers to shift their energy usage to off-peak times. 

• 

Learning energy utilization patterns to recognize potential problems and trigger alarms for vulnerable people. 
Involves providing insurance and healthcare services to a community or individual consumers leveraging from data shared 
from smart meters or non-intrusive load monitoring devices. This could be undertaken by machine learning algorithms to 
analyze energy utilization patterns and identify potential issues. The primary focus could on addressing the needs of senior 
citizens with reduced mobility or disabilities, who lead independent lives but face the risk of accidents such as falls or other 
hazards without immediate assistance available. 

•  DER asset management. Presently, the data collected from operational wind turbines, PV panels, and storage systems 
are accessible only to RES power plant owners and OEMs, which are the only beneficiaries of the knowledge extracted from 
data. However, by exploiting machine learning expertise and other data sources (e.g., robotics inspection, satellite images, 
advanced sensors), access to real operational data allows to support different O&M actions or assess the financial risk of 
new investments. 

• 

• 

Predictability of electrical mobility patterns and charging coordination. Enhancing the predictability of charging 
point availability and EV charging needs is crucial for the effective planning of incentives for EV drivers and the accurate 
estimation of flexibility for aggregators, TSO, and DSO. This involves the integration of data from different sources, including 
charging  points,  mobile  crowd-sensing  platforms,  and  cloud-based  systems  provided  by  vehicle  manufacturers,  among 
others. To accomplish this, it is essential to establish incentive mechanisms that encourage EV drivers and mobility service 
providers to share their data securely and privately with various stakeholders. 

Cross-sector consumer flexibility. The availability of historical and/or operational data from diverse load types, assets, 
and processes across non-energy sectors (such as water, smart cities, mobility, and manufacturing) holds significant value 
in quantifying their flexibility potential and designing effective marketing and engagement strategies for consumers in those 
sectors.  Access  to  such  data  enables  consumers  to  unlock  additional  revenue  streams  through  the  provision  of  system 
services  via  data  sharing.  In  this  context,  multi-energy  infrastructure  planning  plan  would  benefit  from  a  better 
understanding of how the electricity and gas demands are likely to evolve in the context of net-zero communities; the goal 
is the design of incentives to replace gas consumption with electricity.  

14 

 
 
  
 
 
 
 
 
 
 
 
 
 
Energy Data Space 

• 

• 

Energy  efficiency  for  final  users.  Building large datasets with  the  impact  and context of  different  energy  efficiency 
actions at the building and household level is crucial to de-risk investment, and better designing financial support schemes 
and policies. The tracking of assets operation  and corresponding efficiency, via shared data, help users to improve their 
operating strategies and schedules. End-users can utilize data space components for smart carbon accounting and increase 
knowledge on for track-and-trace of energy origin. 

Energy efficiency for industry and sector coupling. Several projects are developing insights into industry retrofitting 
and promotion of renewable energy integration;20 moreover, AIOTI is working on introducing a comprehensive methodology 
to propose a method of calculating the carbon avoided emissions in an industrial sector/domain, when ICT is used as an 
enabling technology.21 All these activities can benefit from the integration with data spaces frameworks. ETIP-SNET WG 1 
recent paper22 related to sector coupling, including the related use cases, data management and sharing needs based on 
the  enabling  platforms  indicated  the  evolving  demand  for  such  exchanges  among  energy  actors.  The  paper  addressed 
aspects  beyond  the  energy  conversion  issues    focused  on  technologies  building  bocks  bringing  planning  and  project 
assessment criteria, regulation and policy needs, architectures and roles, data management and the related infrastructures 
and customer involvement. The wholistic approach proposed in the paper and the related architectures and data needs can 
be addressed by distributed data approach and the emerging paradigms. 

All these use cases share a common vision where data sharing is viewed as a means to generate value from distributed data, without 
necessarily exchanging the data itself. Emerging paradigms, such as federated learning, transfer learning, and digital twins, hold the 
potential  to  create  conditions  for  collaborative  analytics  and  optimization,  enabling  data-enabled  solutions  to  contribute  towards 
decarbonization goals. 

5. Reference data flows 

Data exchange implies the access and sharing of relevant, essential data to activate the flexibility of consumers and prosumers. Data 
sharing and access should consider all relevant actors of the energy value chain including end-users as well as system operators, 
market players and power exchange platforms. The data exchange flows outlined in the Figure 3 have been identified as critical ones 
to enable DSF flexibility transaction across the energy value chain while connecting essential grid and market data spaces to ensure 
transparency and observability across energy actors. 

Figure 3. IEC TC57 Working Group 21: Grid – behind the meter data interactions. 

20 https://re4industry.eu. 
21 https://aioti.eu/wp-content/uploads/2022/11/AIOTI-Carbon-Footprint-Methodology-Report-Final-R1.1.pdf. 
22 Smart Sector Integration, towards an EU System of Systems - https://smart-networks-energy-
transition.ec.europa.eu/sites/default/files/publications/ETIP-SNET-PP-Sector-Coupling-towards-an-EU-System-of-Systems-.pdf. 

15 

 
 
  
 
 
 
 
 
 
 
Energy Data Space 

This  high-level  representation  allows  to distinguish  different  data  exchanges  to  be  associated  to  energy  data spaces.  These data 
exchanges may require synchronous data exchanges or streamed real-time data multi-casted across various service providers and 
system operators. 

• 

• 

• 

Between  Behind-the-Meter  (BTM)  DER  asset  data  space  for  BTM  energy  managements.  DERs  can  consists  of 
different types of flexible devices such as white goods, heat pumps, home batteries, V1G or V2G chargers, as well as Building 
Energy  Management  Systems  (BEMS).  BTM  data  exchange  flows  relate  to  the  ability  of  DERs  to  communicate  between 
themselves.  

Between BTM DER assets (individually or via BEMS) and Flexibility Market Operators through Flexibility Service 
Providers  data  space  for  Market  Participation.  Each  BTM  DER  assets  can  interact  either  individually  and  through 
dedicated  resource  operators,  or  they  can  be  integrated  through  BEMS  allowing  an  optimal  operation  of  a  building,  by 
ensuring communication among individual BTM assets. This data space application is essential to automate DER response 
to implicit signals such as price, grid congestion alert as well as explicit measurement and control data for flexibility service 
providers to bid associated DER’s flexibility into markets. End-users may decide to contract the procurement of a flexibility 
service  from  one  or  several  flexibility  service  providers  (FSP)  for  one  or  more  of  their  DERs,  eventually  via  a  BEMS. 
Harmonization of the standards used for flexibility market interfaces is key to this data flow to enable the exchange of data 
in real-time to untap flexibility potential and accelerate deployment of FSPs at Pan European level.  

Between  BTM  DER  assets  (individually  or  via  BEMS)  and  System  Operators  data  space  for  Grid  Emergency 
Services and Flexible Grid Connection Operation. Some DERs offer fast response flexibility services which, in some 
exceptional grid stability emergency cases or congestion redispatch near real-time, offer direct connection to grid operators 
for observability as well as emergency post-market controls, as already been defined through the ACER grid connection 
codes  for  larger  front  the  meter  DER  assets.  These datasets  are  usually limited  to  significant  grid  users,  which  may  be 
exceptionally operated directly by the DSOs in case of system instability and emergency post-fault measures. 

6. Key challenges implementing Energy Data Spaces in Europe  

Comprehensive analysis on ongoing R&I activities allowed to identify several key challenges, which have to be addressed to leverage 
the deployment of energy data spaces in Europe on a large scale. Particularly, the desk study relates to the work of relevant EU Expert 
Groups  and  legislation,  like  the  EU  Smart  Grids  Task  Force,  as  well  as  via  a  dedicated  questionnaire  that  addressed  relevant 
stakeholders and the activity conducted with the cluster of preparatory actions for energy data spaces: five innovation actions (IA)23 
and one coordination & support action (CSA)24 of the Horizon Europe program. 

In the following sections, the challenges are presented and grouped according to their different categories. In general, the regulatory 
and technical aspects need to be addressed together. When regulatory and technical challenges are separately considered, other and 
perhaps bigger challenges can arise. The main challenge would be constituted by the entire re-thinking of business processes of the 
whole energy sector and market. The data spaces design must consider how traditional market roles must evolve to function in a new 
decentralized digital energy infrastructure, where sector coupling and end-consumers are going to play a central role in grid control 
balancing. 

Technical challenges: data availability and accessibility, technical and information interoperability. 

•  Need for harmonization of data models, ontologies and architectures. Multiple standards are currently in place in 
the energy domain to describe data models and ontologies; as examples, the standards IEC Common Information Model 
(CIM) is currently largely used by Grid, Market operators and has recently been endorsed as an obvious choice by flexibility 
service providers through Smarten as well as, of the ETSI SAREF which is fast developing for the description of behind the 
meter connected assets. In conjunction with these 2 standards, a diverse range of fundamental semantic ontologies has 
been meticulously crafted and harnessed to extensively cover the domain-specific aspects of energy (e.g., ThinkHome25, 
Ontology for Energy Management Applications (OEMA)26, Open Energy Ontology (OEO)27, SEMANCO28 as well as IEC61850-
7 ontology for the description of Smart inverters). Aligning and integrating energy domain specific ontologies to acquire a 

23 DATA CELLAR: https://cordis.europa.eu/project/id/101069694; 
EDDIE: https://cordis.europa.eu/project/id/101069510; 
ENERSHARE: https://cordis.europa.eu/project/id/101069831; 
OMEGA-X:  https://cordis.europa.eu/project/id/101069287; 
SYNERGIES:  https://cordis.europa.eu/project/id/101069839. 
24 int:net: https://cordis.europa.eu/project/id/101070086. 
25 ThinkHome ontology - https://www.auto.tuwien.ac.at/index.php/research-fields/ontology. 
26 OEMA ontology network https://innoweb.mondragon.edu/ontologies/oema/ontologynetwork/1.1/index-en.html 
27 Booshehri, M., Emele, L., Flügel, S., Förster, H., Frey, J., & Frey, U. (2021). Introducing the open energy ontology: Enhancing data interpretation and 
interfacing in energy systems analysis. Energy and AI 2021; 5: 100074. 
28 Corrado, V., Ballarini, I., Madrazo, L., & Nemirovskij, G. (2015). Data structuring for the ontological modeling of urban energy systems: The experience 
of the SEMANCO project. Sustainable Cities and Society, 14, 223-235. 

16 

 
 
  
 
 
Energy Data Space 

level of consistency and interoperability, ultimately depends on the specific use cases and requirements of each ontology 
and how they are designed to interoperate with others. In the existing scenario the achievement of interoperable solutions 
does not strictly depend on the creation of new standards and data models (except for new technologies) but, in most of 
the cases, on the mapping among different data models and standards. Specifically, the upcoming new business models 
associated with the data spaces will favor interconnection of different sectors (mobility, heating/cooling, city in conjunction 
electrical  grids, at  region  and  national  level)  and  operational  functionalities  that require  interoperability  of data  models 
among newly interconnected applications. Additionally, a common view on how to integrate reference architectures such as 
GAIA-X and DERA 3.0 should be defined for the implementation of an interoperable energy data space bridging behind the 
meter  assets  with  Grid,  Market  and  Service  providers  ontologies  derived  from  CIM  (particularly,  a  common  vision  on 
federation of different data spaces across domains as well as countries and at pan European level is still lacking. 

Accessibility  of  data:  smart  meters  and  DER  dedicated  measurement  devices.  The  achievement  of  flexibility 
mechanisms  through  the  data  spaces  entirely  relies  on  an  efficient  and  smooth  sharing  of  data  from  each  data  space 
participant, including the end-users. The European directive 2019/94429 and the new C(2023)347730 specify rules for TSOs 
and DSOs in regards to data from dedicated metering devices. Anyway, in the current situation, the access to smart meters 
data, which need to be viable for all main Advanced Metering Infrastructures (AMI) concepts, is still restricted and, hence, 
concrete  actions  on  this  matter  are  required.  Moreover,  specifications  on  the  quality  and  resolution  of  shared  data  for 
Distributed Energy Resources have to be reinforced. Similarly, equivalent challenge involves the accessibility of data in the 
e-mobility, as well as storage and heating domains, particularly on the state-of-charge of EV or batteries used for PV self-
consumption as well as any heat storage used in combination with Heat Pumps; in this respect, definition of usage rights 
like planned in the Data Act are necessary. 

Identity management in the data spaces architecture. The identity manager component has a fundamental role in 
the domain specific or domain-agnostic reference architectures: ensuring the trust among data exchange actors and the 
respect  of  governance  agreements.  The  conventional  implementations  of  data  spaces  position  the  identity  manager 
component in the central, organizational levels. Anyway, for specific energy use cases there is the need to integrate the 
identity managers components at the end-user level of the data space ecosystem (e.g., in a local energy community, directly 
at  the  community  members),  in  order  to  allow  advanced  development  of  marketplaces.  Electronic  Identification  and 
Authentication Services (eIDAS)31 and eIDs represent promising options for a common European pillar for reliable I&A across 
all Member States. With its upcoming amendment, representation of natural persons by other natural persons and legal 
persons by natural persons will be provided, which would make it an obvious candidate to connect Data Spaces from the 
I&A perspective. 

Role  of  metadata.  Advanced  grid  services,  including  flexibility  and  demand  response,  enabled  by  data  shared  in  the 
ecosystem rely, in addition to electrical measurements and power system quantities, on various categories of metadata. 
Although the maturity level of data models of electrical grid data is already advanced, the lack of formalized mechanisms 
for introducing metadata is still open and requires further developments to be able to take advantage of the reference CIM 
ontologies used across the Grid, market and flexibility service provider domains. Some progress has been achieved through 
ONENET32 and its associated market participant connector leveraging IEC62325 and IEC62756 ontologies. 

• 

• 

• 

•  Use of AI technology. The commercial use of AI, which is particularly critical for the success of data spaces33, is prevented 
by the current draft status of the AI Act34, in particular Art. 10 Para. 3. as these exclusively require "relevant, representative, 
error-free  and  complete  training,  validation  and  test  data  sets".  Such  databases  are  practically  non-existent  because  a 
minimum error is intrinsic in the model; for this reason, specific regulatory actions need to be undertaken. 

Organizational challenges: governance, data value and business aspects. 

• 

Federation of data spaces in the ecosystem. The strategy to connect pan European domain specific data spaces with 
country level sub-data spaces needs to be defined. Ideally, considering the different use cases in the energy domain that 
lead to deployment of multiple data spaces, the viable path aims at a federated data spaces ecosystem that is constituted 
of several interoperable data spaces leveraging common semantic and ontologies. According to this approach, the future 
pan European energy data space corresponds to a common unique framework with defined governance mechanisms as 
well as specific architecture and set of building blocks using a pivot data models across country specific data spaces with 
different shared data content and instances according to the specific use case. The interconnection of different data spaces 
will be also accompanied by the mutual discoverability and accessibility through common data dictionaries such as CIM or 
SAREF4ENER, with benefits for every stakeholder. 

29 Directive (EU) 2019/944 of the European Parliament and of the Council of 5 June 2019 on common rules for the internal market for electricity and 
amending Directive 2012/27/EU. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32019L0944. 
30 C(2023)3477 “Implementing regulation for access to metering and consumption data” https://energy.ec.europa.eu/publications/implementing-
regulation-interoperability-requirements-and-non-discriminatory-and-transparent_en. 
31 eIDAS Regulation - https://digital-strategy.ec.europa.eu/en/policies/eidas-regulation. 
32 OneNet - One Network for Europe https://onenet-project.eu/. 
33 IEA https://www.iea.org/commentaries/why-ai-and-energy-are-the-new-power-couple. 
34 Proposal for a Regulation Of The European Parliament And Of The Council Laying Down Harmonised Rules On Artificial Intelligence (Artificial 
Intelligence Act) And Amending Certain Union Legislative Acts https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A52021PC0206. 

17 

 
 
  
 
 
 
 
Energy Data Space 

• 

Business models of data intermediaries. Acknowledged soft infrastructures of data spaces, at cross-sectoral and cross-
country level, include in their reference architectures specific roles for intermediaries positioned between the data user and 
the data owner (i.e., federation services and required services for the operation of data spaces, as data or service provider 
and data consumer). As a challenge, the development of energy data spaces must account for a dedicated analysis, and 
consequent validation, of business models for the intermediaries. 

•  Mechanisms for the long-term maintenance of the data space. In the design phase, risks and countermeasures to 
possible issues must be considered and included in the governance rules. For example, the abandonment of the data space 
by  a  required  intermediary  (e.g.,  clearing  house,  governance  body  or  service  provider)  shall  be  addressed  so  that  the 
functioning, trust and security of the ecosystem is not compromised. Moreover, the evolving technologies and it implications, 
such as AI, will necessitate dynamic regulatory approach within the context of data spaces, which could also assume role 
of regulatory sandboxes. 

• 

Alignment of European legislation at member states level. Data spaces will benefit from the data sharing among 
entities located in different geographical areas, as different European member states. The different forms and transposition 
of  European  legislation  in  every  member  state  involves  diverging  conditions  that  could  compromise  the  homogeneous 
accomplishment of governance, operational and business agreements. In fact, European regulations for energy consist in a 
complex integration of member state and pan European legislation with sometimes diverging definitions , leading to complex 
alignment process between "bottom-up"-approach and pan European legislations such as the Clean Energy Package and 
RepowerEU. Steps have been taken recently to improve such alignment through ENTSO-E and EU DSO joined working group 
for energy and flexibility data interoperability leading to the definition of a new harmonised role model defining actors roles 
and so setting solid bases to define data exchange (as reused for instance through the DERA architecture model). 

Social challenges 

• 

• 

Trust. Companies present concerns about revealing their know-how by sharing their data, hence, gaining their trust in data 
spaces will be a major challenge to overcome. Moreover, an energy data space design will need to comply with regulations 
on  personal  data  (e.g.,  GDPR)  and  consider  that  some  data  cannot  be  made  openly  available without  anonymization  or 
citizen formal consent. Next to the protection of personal data, the governance of data spaces should also address the issue 
of data ownership, to recognise latest data act developments especially regarding end user data ownerships principles. It 
will be necessary to develop technological solutions to ensure sovereignty, control over data usage, security and privacy. 

Involvement of end users. The full involvement of end users’ participation requires specific enforcement measures and 
transparency to end users on associated data usage. An existing barrier is the current users’ tendency to consider the data 
as “their power, compromised by its sharing”; hence the crucial importance to set up proper operational mechanisms for 
consent  management  clearly  highlighting  reciprocal  business  advantages  (for  both  parties  covering  both  monetary  and 
indirect benefits). Moving forward, energy dataspaces should ensure end user are fully aware of the trustworthiness of the 
data space, corresponding to the full achievement of security, privacy and confidentiality of data sharing. 

•  Data valorisation challenges: seamless incentive mechanisms and data markets covering B2B and B2C scenarios.  To 
enhance  data  sharing  in  both  B2B  and  B2C  scenarios,  it  is  crucial  to  establish  seamless  incentive  mechanisms  and 
marketplaces.  In  the B2B context,  promoting  the  development of fair  data monetization  strategies,  incorporating digital 
technologies like Blockchain, and implementing data-by-data exchange strategies are vital. While open data initiatives hold 
value and advantages for some data of common interest, sustainable business models for data sharing platforms require 
assessing data’s value based on its specific use cases. In the B2C setting, the involvement of social sciences and humanities 
(SSH) becomes essential in designing engagement strategies that encourage lifelong data sharing and consumer digital 
twins.  Here,  the  data  shared  by  the  customers,  with  service  providers  and  among  themselves,  have  a  value  that  is  not 
necessarily economic but, as alternative, can enable specific services for the customers themselves (e.g.,  in the domain-
agnostic  digital  environment,  the  customer’s  data  on  its  position  allows  to  define  the  traffic  information,  beneficial  for 
herself/himself). In this regard, the following categories are identified: 

o  Data-by-money (monetary incentive): data owners accept to share their data because they are financially 
compensated if their data is relevant for solving analytics/optimization tasks and pay in case data from the others 
is relevant to their own tasks. This approach is more suitable for the B2B or B2B2C context (such as for Flexibility 
Service provider). 

o  Data-by-data (non-monetary incentive): barter trading, specifically a data-by-data exchange scheme for non-
monetary  compensations.  There  is  no  money  involved  and  data  owners  agree  to  share  and  receive  data  with 
approximately the same value; exchanged data includes services as, for example, alarm signals, fault notifications 
and indications of maintenance actions. This approach is applicable to both B2B and B2C contexts. 

o  Apply  an  SSH-driven  approach  to  combine  the  sharing  economy,  co-creation,  and  design  thinking 
methodologies and place energy consumers (data owners) at the forefront. The goal is to actively involve 

18 

 
 
  
 
 
 
 
 
 
 
and inspire consumer panels to share their energy data, leveraging from: i) offer consumer-centric value-added 
data-enabled  services  and  ii)  explore  innovative  and  decentralized  data  governance  roles  within  the  dynamic 
interaction between data and energy value chains. 

Energy Data Space 

7. Policy and regulation recommendation 

Starting from the challenges and risks to be considered for the effective deployments of data spaces, which have been described in 
the previous chapter, policy and regulation recommendations have been derived. These recommendations aim to propose tangible 
and  specific  measures  to  leverage  the  uptake  of  data  spaces.  Even  if  primarily  defined  for  the  energy  domain,  specific 
recommendations can be transposed to cross-domain deployments. 

Recommendations on regulatory measures and standardization. 

• 

• 

• 

Foster harmonization of mechanisms and standards. Although new technologies require effort in developing new 
dedicated standards, most of the energy use cases deploy data models, ontologies and functionalities that are already 
covered by existing standards with a predominance of CIM, SAREF4ENER and OCPP; in this latter condition, the main 
requirement  consists of  extensive alignment  of existing  technical  regulations  and  standards.  Hence  investments on 
effective and long-term harmonization mechanisms are necessary, not only at the energy domain but also on a domain-
agnostic perspective. At this scope, it is necessary to continue effort on developing standards and data models through 
the Bridge initiative; the landscape report35 on energy and flexibility data models and interoperability across the sectors 
of energy, mobility and buildings gives guidance and directions on eligible standards and models. Additionally, the real-
time capabilities in standard communication protocols (e.g., REST, HTTP, Kafka, MQTT) should be enhanced to cover Grid 
operator observability requirements. 

Cooperation among European initiatives. It is strongly recommended to foster cooperation among the different 
European initiatives in the energy domain and define a roadmap for the development of data spaces at EU level. This 
action must be accompanied by the target of a homogenous level of digitization in the energy system. Two parallel 
directions shall be pursued: (i) establish priorities and implement them in each country under a harmonized European 
framework and (ii) follow the sectoral development; (for example, from the system operators who should work together 
to create successful developments with the vision of the industry). "One pager" about the visioned data is required, 
which the member states could use in further spreading the understanding. Decentralized approaches like national data 
spaces are easier to be initiated, but in the long run these initiatives need to be integrated through pivot pan European 
dataspace federation, avoiding the use of a centralized authority approach as originally developed. In case centralized 
approaches are considered in some countries, the associated work should be jointly defined and accepted by all relevant 
parties – from Grid and Market Operator to Flexibility Service Operator down to DER operators and aggregator through 
a transparent, clear and easy to understand pool of current knowledge as well as validated roadmaps that consider co-
dependencies as well as interactions (market-operations-assets) over different time-horizons are necessary. 

Regulation  for  the  functioning  of  data  markets.  The  Joint  Working  Group  Data  Interoperability  organized  by 
ENTSO-E and EU DSO Entity, which has been established on recommendation by Implementing Regulations following 
the  Art.  24  of  EU  Directive  2019/944,  aim  to  improve  interoperability  requirements.  There  is  an  existing  need  for 
regulating  local  energy  markets  and  flexibility  markets,  to  guarantee  effective  benefits  for  the  prosumers.  As  a 
recommendation applicable but not limited to the energy domain, the data sharing agreements and templates, legally 
binding participating in data sharing, shall be formalized through that group which needs to be expanded to the other 
market participant stakeholders to ensure an end-to-end validation of associated concepts (as established through the 
flexibility network code drafting). Particularly, it is recommended to define both pan European transverse regulatory 
frameworks across member states for the management of common pan European data sets for the management of 
pan European legislations (such as for instance the one required for data interactions with mass produced DER sold 
across Europe such as EV chargers, residential storage or heat pumps), while considering local country specific data 
spaces  integrating  data  related  to  each  member  state  specific  regulations.  At  this  scope,  regulatory  and  technical 
sandboxes are considered fundamental for fostering new digital infrastructure and market roles and define minimal 
interactions across dataspace partitions. In general, the energy data space should be composed of federated country 
level  data  spaces  and  be  flexible  enough  to  facilitate  implementation  in  each  EU  country  while  at  the  same  time 
standardized enough to ensure cross-country interoperability for certain legislations such as the flexibility code. 

• 

Avoidance of vendor and initiative lock-ins. To foster the technology advancements, the benefits for the users 
and  the  data  spaces  deployment,  the  regulatory  framework  shall  support  competition  and  disruptive  innovation, 
avoiding customer lock-in to vendors and initiatives. It should furthermore facilitate the reuse of Opensource libraries 

35 Landscape report on energy and flexibility data models and interoperability across the sectors of energy, mobility and buildings https://digital-
strategy.ec.europa.eu/en/library/landscape-report-energy-and-flexibility-data-models-and-interoperability-across-sectors-energy. 

19 

 
 
  
 
 
 
 
 
 
 
Energy Data Space 

as developed through European Research project to ensure the fastest innovation to market. Future Research projects 
should furthermore be guided to maximize the reuse of these dataspace to minimize development duplications on core 
infrastructures. 

• 

Implement data protection regulatory and measures in confines of data spaces: On top of the existing EU 
legislation concerning data protection and privacy (e.g., EDPS,36 the 2016/67937 regulation, etc.), it is recommended 
that  state-of-the-art  principles  should  be  defined,  through  the  design  and  development  of  data  spaces  including 
consumer owned data, and integrating privacy and data protection principles from the outset. This includes recognizing 
advanced privacy measures scoping the entire lifecycle as well as defining necessary data portability measures in case 
consumers opt for different service providers. On top of that, blockchain technologies should be considered as an option 
to ensure secure and decentralized data sharing when use cases require such an approach. Implementing federated 
learning  techniques  for  instance  allows  for  collaborative  analysis  without  centralized  data, minimizing  privacy  risks 
associated with data sharing. By implementing these measures, the EU can demonstrate its commitment to robust 
data privacy and protection in data spaces, fostering trust, security, and innovation. 

The proposed data categorization aims to outline which energy-related data could be considered: 

o 

o 

o 

o 

highly sensitive data, which cannot be shared, to preserve the security of the energy system; 

critical  and  sensitive  data,  requiring  specific  agreements  between  parties  and  the  highest  level  of 
confidentiality and protection measures; 

public data, which can be shared for no, or minimal fee; 

exchangeable data, not requiring specific protection measures to be shared via B2B or B2C agreements 
(with the exception of data of the same kind that qualify either as highly sensitive or critical sensitive). 

All types of data not belonging to the previous classifications (highly sensitive, critical and public), will be considered 
‘exchangeable’. 

•  Data  with  high  quality  in  dataspaces:  The  EU  demonstrates  its  commitment  to  data  quality  assurance,  as 
exemplified  by  the  effort  conducted  under  ACER38  quality  assurance  to  establish  high-quality  transaction  and 
fundamental  data  reporting.  To  address  the  evolving  requirements  of  data  spaces,  it  is  imperative  to  develop 
frameworks and guidelines that specifically highlight data quality considerations. A cutting-edge approach to achieving 
this  is  by  harnessing  the  power  of  Machine  Learning  (ML)  and  Artificial  Intelligence  (AI)  algorithms.  Training  these 
models to detect anomalies, outliers, and data discrepancies, organizations can proactively identify and resolve data 
inaccuracies, thereby enhancing data quality. 

Recommendations on investments and infrastructures. 

• 

• 

• 

Continuity of the data spaces. A major risk in the functioning and running of established data spaces corresponds 
to  the  abandonment  of one  or  more  key  actors  (e.g.,  governance  bodies,  data  providers,  intermediaries).  Dedicated 
supporting measures shall be established to minimize the effects of such situations for end-users and enterprises. 

Openness of standards and interfaces. To accelerate the knowledge sharing in the community and the development 
of new technologies and solutions, dedicated investments shall support the usage of open standards and the open APIs 
(e.g.,  interfaces  for  seamless  onboarding  of  data).  It  is  noteworthy  that  open-source  elements  of  data  spaces  are 
available but not finalized yet and not customized for the needs of the energy sector. 

Federated data spaces infrastructures. A federation approach for data spaces is needed: the goal is to identify, 
connect and streamline the existing country level and domain specific data spaces and infrastructures in a bottom-up 
way. In doing so, federated infrastructures shall be able to accommodate not only data spaces but also key data hubs, 
platforms,  distributed  services  and  applications.  Additionally,  this  orchestration  of  federated  infrastructures  shall 

36 European Data Protection Supervisor (EDPS) https://european-union.europa.eu/institutions-law-budget/institutions-and-bodies/search-all-eu-
institutions-and-bodies/european-data-protection-supervisor-edps_en.  
37 Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the 
processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) (Text with 
EEA relevance) https://eur-lex.europa.eu/legal-
content/EN/TXT/?uri=uriserv%3AOJ.L_.2016.119.01.0001.01.ENG&toc=OJ%3AL%3A2016%3A119%3ATOC. 
38 ACER data quality - https://www.acer.europa.eu/remit/data-collection/data-quality. 

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Energy Data Space 

consider the establishment of one or more registers for federated data spaces, each of which comply with dedicated 
certification. 

Particularly, federation and linkage of data-sharing infrastructures should be supported by: 

o 

o 

o 

o 

Re-utilizing, to the highest degree, the existing deployments. The development of energy data spaces at national 
level must be compatible with a superordinate data space at European level. 

Alignment with the European approach to energy service interoperability expressed by Implementing Regulation 
(EU) 2023/1162 and follow-up acts, realizing the mandates given by Directive (EU) 2019/944, especially Articles 
20-24.  

Promoting a broad application of eIDs and EIDAS while ensuring that natural persons can represent legal persons 
and  other natural  persons. Common means  for  identification  and  authentication  between  member  states  (and 
between  data-sharing  infrastructures)  must  be  a  core  pillar,  as  highlighted  in  the  communication  “European 
Strategy for Data”. 

Ensuring a well-defined mandate for data-sharing infrastructure operators, publicly available, clean and structured 
interfaces. 

•  Hardware  infrastructures.  Considering  the  extra-large  volume  of  data  that  needs  to  be  exchanged  and  stored  in  a 
distributed  fashion,  with  performant  computational  requirements,  dedicated  infrastructures  (e.g.,  scalable  cloud-based 
combined with cognitive computing and edge solutions) are necessary and have to be realized. Particular attention must be 
placed on the energy consumption of the ICT sector, as stated in the “Digitalising the energy system - EU action plan”: the 
adoption of technologies with low electricity consumption as well as circular models have to be prioritized. Outcomes of 
data and the related infrastructure models, such as CEI39 focused on devising optimal edge to cloud computing continuums 
that should be considered, since one of the goals is prioritisation of data models at all enabling nodes. 

• 

Funding of data spaces deployments. Bottom-up development of federated data spaces shall be achieved with public 
fundings addressing initiatives focused on specific use-cases as well as large horizontal ones to support pan European key 
legislations  derived  from  the  Clean  Energy  Package,  RePowerEU  and  the  new  Electricity  Market  Design.  Moreover,  the 
sustainable funding of established solutions at the long run, rather than of new data spaces instances, shall be ensured to 
prioritize the focus on users’ needs. 

•  Measures to ensure the participation of consumers. Specific measures must be put in place to reassure the consumers 
regarding  the  reliability,  security,  and  privacy-compliance  in  the  sharing  of  their  own  data.  Economic  benefit  for  the 
consumers consists of appropriate incentives, allowing to get back part of the investment in clean and smart technologies; 
in addition to developing consumer-centric solution, the technology shall be also affordable to all. Non-monetary benefits 
entail  environmental  advantages  and  are  based  on  the  social  and  behavioural  needs.  For  example,  the  development  of 
dedicated mobile applications and Graphical User Interfaces (GUI) for control of private energy assets consists of a reference 
starting point. Anyway, additional comprehensive instructive sessions on digitalization and energy solutions concepts, with 
dedicated tools, shall be continuously carried out. 

•  Data  privacy  infrastructure.  To  ensure  secure  data  storage  and  transmission,  a  robust  infrastructure  with  strong 
encryption protocols and secure communication channels must be established. This includes utilizing secure cloud storage 
solutions, implementing end-to-end encryption, and adopting secure data transfer protocols to protect data during storage 
and transmission. Regarding the access controls and user authentication, stringent related mechanisms shall be deployed 
to ensure that only authorized individuals can access and manipulate sensitive data. At this scope strong user authentication 
methods, such as multi-factor authentication, and role-based access controls are needed. 

39 CEI project https://eucloudedgeiot.eu/about/.  

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References 

•  Weigert, A., Hopf, K., Günther, S. A., Staake, T. (2022). Heat pump inspections result in large energy savings when a pre-

selection of households is performed: A promising use case of smart meter data. Energy Policy, 169, 113156. 

• 

• 

Goncalves, C., Pinson, P., Bessa, R. J. (2021). Towards data markets in renewable energy forecasting. IEEE Transactions 
on Sustainable Energy, 12(1), 533-542. 

Heymann, F., vom Scheidt, F., Soares, F. J., Duenas, P., Miranda, V. (2021).  Forecasting energy technology diffusion in 
space and time: Model design, parameter choice and calibration. IEEE Transactions on Sustainable Energy, 12(2), 802-
809. 

•  Wang, Z., Li, P., Zhou, Y., Wu, J., Zhang, C., Zeng, P., et al.  (2023). Coordinated configuration strategy of multi-energy 

systems based on capacity-energy-information sharing. Energy, 277, 127699. 

• 

• 

• 

• 

• 

• 

European Commission - Directorate-General for Energy “Implementing Regulation (EU) 2023/1162 on interoperability 
requirements  and  non-discriminatory  and  transparent  procedures  for  access  to  metering  and  consumption  data”, 
C(2023) 3477. 

Directive (EU) 2019/944 of the European Parliament and of the Council of 5 June 2019 on common rules for the internal 
market for electricity and amending Directive 2012/27/EU.  

Commission  Implementing  Regulation  (EU)  2023/1162  of  6  June  2023  on  interoperability  requirements  and  non-
discriminatory and transparent procedures for access to metering and consumption data. 

Data Spaces Support Centre - DSSC Glossary - Version 1.0 | March 2023. 

EC-blueprint,  European  Commission,  First-Generation  Blueprint  for  a  Common  European  Reference  Framework  for 
energy-saving applications, https://digital-strategy.ec.europa.eu/en/news/first-generation-blueprint-common-european-
reference-framework-energy-saving-applications, 2023. 

AIOTI,  Guidance  for 
content/uploads/2022/09/AIOTI-Guidance-for-IoT-Integration-in-Data-Spaces-Final.pdf, 2022. 

IoT  and  Edge  Computing 

Integration  of 

the 

in  Data  Spaces,  https://aioti.eu/wp-

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In person 

GETTING IN TOUCH WITH THE EU 

All over the European Union there are hundreds of Europe Direct centres. You can find the address of the centre nearest 
you online (european-union.europa.eu/contact-eu/meet-us_en). 

On the phone or in writing 

Europe Direct is a service that answers your questions about the European Union. You can contact this service:  
—  by freephone: 00 800 6 7 8 9 10 11 (certain operators may charge for these calls),  
—  at the following standard number: +32 22999696,  
—  via the following form: european-union.europa.eu/contact-eu/write-us_en. 

Online 

FINDING INFORMATION ABOUT THE EU 

Information  about  the  European  Union  in  all  the  official  languages  of  the  EU  is  available  on  the  Europa  website 
(european-union.europa.eu). 

EU publications 

You  can  view  or  order  EU  publications  at  op.europa.eu/en/publications.  Multiple  copies  of  free  publications  can  be 
obtained by contacting Europe Direct or your local documentation centre (european-union.europa.eu/contact-eu/meet-
us_en). 

EU law and related documents 

For access to legal information from the EU, including all EU law since 1951 in all the official language versions, go to 
EUR-Lex (eur-lex.europa.eu). 

Open data from the EU 

The portal data.europa.eu provides access to open datasets from the EU institutions, bodies and agencies. These can be 
downloaded and reused for free, for both commercial and non-commercial purposes. The portal also provides access to 
a wealth of datasets from European countries. 

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The SPRING EU Service Contract (n. 300003009) supports ETIP SNET activities, funded by the EU. 

ISBN 978-92-68-10945-8