This is Icebreaker One’s response to the Department of Energy Security & Net Zero Developing an energy smart data scheme call for evidence. Please note that throughout this consultation, Icebreaker One uses the terms Open, Shared and Closed data as defined here.

If you have any questions please do not hesitate to contact us via policy@ib1.org.

Call for evidence response:
1. What are your views on the benefits of an energy smart data scheme? This might include (but is not limited to) benefits to customers, decarbonisation, the economy and wider society

Icebreaker One (IB1) is a non-profit working on data sharing and sustainability, convening organisations and governments to design market-scale solutions to make data work harder to deliver Net Zero. IB1 creates and runs programmes to reduce barriers and costs to finding, accessing, using, and sharing data, which will ultimately reduce costs for consumers.

Supporting a Net Zero economy

The economic case for improved data sharing is compelling. Research demonstrates significant return on investment:

  • Research from the Open Data Institute showed open data (either fully open or shared) delivers overall economic growth
  • Across the EU, re-use of open data to create new services and products was valued at €22bn in the public sector alone in 2020, with €1.7bn in cost savings (€262m in the UK). 

The Clean Power Plan supports the growth mission set out in the Industrial Strategy to deliver economic growth in every part of the country and improve the lives of Britain’s workforce. Clean energy industries represent a substantial potential growth area, with 90% of global GDP covered by net zero targets. The latest CBI Economics report found the “net zero economy is a powerhouse of job creation and economic expansion with 10.1% growth in the total economic value supported by the net zero economy since 2023”.

The shift to a clean power system by 2030 forms the backbone of the transition to net zero and there is measurable importance in having a joined up approach to unlock the widest range of potential benefits during this shift. Cross-sector thinking is required to achieve the size of impact that the Industrial Strategy and The Clean Power Plan have outlined.  

Meeting the UK’s Net Zero goals

Achieving net zero and delivering the British Energy Security Strategy means addressing all aspects of the energy trilemma: affordability, security, and sustainability. The financial, energy and transport sectors are critical first priorities as the UK transitions to a decentralised, green energy future that can be reliably supported by the financial sector. Unlocking access to data through Smart Data schemes will serve to enable, and derisk, these priorities. The UK’s Net Zero goals require continuous information flows throughout project lifecycles, and achieving this will require data-sharing at a scale for decision making and incentivising ‘green’ investment. 

A transition away from fossil fuels to a clean energy system will provide investment, employment opportunities, and help meet the UK’s climate and nature targets. Rebuilding natural infrastructure whilst simultaneously building the new energy infrastructure needed, this could come in the form of creating new wildlife corridors alongside or underneath linear energy infrastructure. 

Integrating systems data 

An energy smart data scheme needs to address broader systems data to deliver a flexible, decentralised, and digitalised energy system that is critical to Net Zero. The UK’s energy system will be increasingly challenged by a growing renewable mix, shifting and unpredictable demand on the grid, and the emergence of widely distributed prosumer and demand response energy resources. For example, currently energy is being wasted due to there not being enough capacity to transport or store electricity produced by wind and solar farms. An energy smart data scheme allows for space for thinking between the UK’s industrial strategy, and net zero goals, and growth areas. 

The Seventh Carbon Budget (2038-2042) highlights the role of surface transport and energy supply in achieving the UK’s emissions reductions targets, which will require a 23.2% reduction in energy sector emissions and a 26.5% reduction in transport emissions over the period 2023 – 2037.  To meet these goals, an energy smart data scheme must facilitate the decarbonisation of transport through electrification and demand-side flexibility in energy supply. Smart meter insights can optimise grid integration for EVs, improve energy efficiency in buildings, and accelerate the transition to decentralised, low-carbon power systems, ensuring a resilient and cost-effective net-zero pathway.

A framework for trusted data sharing will unlock the increasing variety, veracity and volume of energy data to system participants to adapt, evolve and create services that enable better network management, and respond to rapidly changing patterns of energy supply and demand.

Cross sector collaboration

It is essential there is cross-sector collaboration, joined up thinking between the UK’s industrial strategy, approach and net zero goals, and growth areas to enable shared best practices. This requires not only better data sharing for the purposes of planning, but also better cross-sector communication, including between departments, regulators, agencies, industry bodies, and industry. 

Specific customer impact and benefits will vary depending on the identified and prioritised use case. IB1 delivers business-driven use cases that can scale efficiently and securely. 

Benefits of taking use case driven approach:

Through IB1 programmes and years of expertise, IB1 supports following a use case approach to data sharing initiatives. This approach centres user needs, makes a business case for the effort of data sharing, and allows for:

  1. Market incentives: there must be an economic argument that policy can then amplify or mandate. If there is no financial incentive, there will be no movement.
  2. Removal of transactional friction: There must be “something in it” for everyone, or at least a path to cost reduction or a new business model. Removing friction can help everyone go together: this is never a ‘technology problem’ (e.g. absence of a data ontology).
  3. Documentation with the identified problem statement, actors and stakeholders, a clear goal, and the envisaged impact. 

To maximise the benefits, use cases must:

  • Address governance, user needs, business, social, legal, engagement and communications to ensure the solution is fit for purpose, and can be adopted by the market. IB1 observes that technical-led programmes tend to fail to gain traction or deliver against material user needs.
  • Foster a community to ensure there is cross-sector collaboration. IB1 strongly recommends taking a joined up approach which is interoperable with initiatives across the economy. IB1 suggests defining relationships with adjacent bodies in the energy sector and beyond to enable cross sector interoperability.

Examples: energy data sharing schemes 

Example: Energy Sector Data Sharing Programme – Open Energy

Through Icebreaker One’s (IB1) UKRI Modernising Energy Data Access competition-winning programme Open Energy, IB1 identified and articulated the need to make it straightforward to find, access and share energy data. Through three phases, IB1 convened 100s of organisations, 500+ public webinar attendees, and over 80 Steering and Advisory Group members to develop operational services for search and access control that are now live and market-facing, and have set the foundations for an Energy Trust Framework. 

Open Energy makes it easy to search (via https://openenergy.org.uk), discover, access and securely share energy data using a Trust Framework and any Schemes which are built within the Trust Framework context. It covers Open Data, commercial Shared Data with pre-authorised access controls, and commercial Shared Data where access requires end-user permission/consent.

See relevant energy use cases in question 14.

Example: Cross-sector data sharing programme – Perseus 

Icebreaker One convenes the cross-sector Perseus Scheme (ib1.org/perseus) to enable automated carbon emissions reporting for every SME in the UK. It creates the rules and processes that make automated reporting possible to enable products and services such as accounting platforms, emissions calculators, and reporting software to be developed that deliver higher-quality emissions data at scale. Perseus convenes hundreds of cross-sector organisations to ensure user needs and barriers from across the supply chains are captured and incorporated into the Scheme. 

2. What can we learn from Open Banking that would be helpful to consider when developing an energy smart data scheme? This might include (but is not limited to): phasing, structure, funding, participation, growth, implementation or governance.

Open Banking is a case study for engagement for Smart Data. It has over 10 million users and over 22.1 million transactions per month. This provides strong evidence that there is both appetite and capability for British consumers to engage with Smart Data utilising a Trust Framework approach. 

It is essential that Open Banking is viewed holistically – an entity incorporating technical, communications, engagement, legal and ongoing governance arrangements – rather than a technical solution.

IB1’s foundational work on Open Energy, Open Net Zero and approach to data sharing is based on the foundations of Open Banking. IB1 practises this through:

  • Decentralised architecture implementation
  • Advocating for common secure web standards (i.e. FAPI)
  • Openly published rules and clear governance structure 
  • Openly list service providers are available
  • Providing member services 

A key learning from the success of Open Banking is to follow a use case driven approach (see question 1 for benefits). See more information on the development of UK Open Banking here: https://dgen.net/0/2018/04/04/report-development-of-uk-open-banking/ 

3. What can we learn from international examples of Smart Data schemes for our approach in the energy sector? 

International examples of data sharing initiatives (not all smart data schemes)

General lessons from national and international data sharing initiatives: 

  • Incorporate governance at the outset. It is difficult to retroactively implement robust governance.
  • Ensure governance is robust, participatory and responsive. It will be required to adapt to a full spectrum of social and environmental considerations shaping the operational landscape. A governance model must reflect the socio-technical nature of the energy sector, not just the technical side.
  • Avoid putting too much emphasis on a technical solution  – An energy smart data scheme must equally address governance, user needs, business, social, legal, engagement and communications to be successfully implemented and ensure the solution is fit for purpose.
  • Complexity and collective agreement across the industry – an initiative must recognise the complexity and changing nature of the energy industry.
  • Cultural change and industry readiness – must understand and interact with the current data sharing culture within the energy companies, and consumers must be engaged to understand their value proposition. 
  • Appropriately defining and governing the roles and responsibilities.
  • Appropriate legal support and resourcing – a mechanism must develop the applicable data licences, and needs to be appropriately resourced to be able to do so. 
4. What additional value could an energy smart data scheme deliver alongside existing data sharing initiatives? Please include your views on how an energy smart data scheme might support or hinder existing data sharing and digitalisation initiatives.

Energy data is currently hard to access (it is not ‘digital ready’ and requires multiple bilateral requests and contracts). It is disconnected from related sectors. An open standards-based, transparent, market-wide framework can allow rapid scalability of secure access to data. 

As mentioned in IB1’s response to the Department for Business and Trade’s Invest 2035 consultation, it is essential to have consistency within sectors and across the pinchpoints where sectors meet and/or markets are increasingly ‘coupled’ (i.e. energy and transport; energy and water; energy and manufacturing). It is essential that an energy smart data scheme promotes interoperability and consistency across sectors, promoting a whole-system approach to digitalisation and net zero.

In 2021, IB1 was commissioned by BEIS (DESNZ) to report on How Smart Data can help unlock a Green Economy. It explored a representative cross-section of use cases, and prioritised where impact (environmental and economic) meets achievability (lower level of regulatory and technical complexity). Key learnings include:

Smart Data becomes effective when it is connected

In terms of prioritisation of sector, use cases requiring cross-sector interoperability and cohesion offer the greatest immediate ability to create impact, with a manageable degree of complexity involved in rollout. These use cases support private sector growth and require achievable government intervention, allowing green growth and environmental goals to be met.

Cross-sector engagement is essential

Every sector has something to offer – and cross-sector engagement is necessary in order to achieve policy aims. 

5. What energy customer needs could potentially be addressed by an energy smart data scheme? 

As mentioned in question 1 and 2, user and customer needs should be identified through a robust governance process which can understand, process, and define use cases with relevant stakeholders. In IB1’s Scheme governance (standard operating procedures), IB1 emphasises the importance of having a user needs & impact advisory group which explores, prioritises, and works through use cases (including identifying users, their needs, and mapping data value chains). This process allows for the development of business, value, and impact cases and their impact on policy, businesses, and financial instruments. 

As mentioned in question 1 and 14, IB1 has identified and documented a wide range of use cases and benefits associated with trusted energy data sharing.

As noted in the Clean Power 2030 Action Plan, central to delivering decarbonisation in the energy system is ensuring it benefits consumers and businesses. The UK needs to protect and empower consumers, provide stability for businesses and ensure confidence for investors. 

6. Which customer groups might benefit most from an energy smart data scheme and why? 

While all consumers should benefit from having a lower cost, efficient energy system which is resilient to geopolitical shocks due to an energy smart data scheme and improved data sharing. Those who will benefit the most from the system efficiencies and energy price cost reduction will be low-income households who are unable to make ‘green’ investment on their own due to the upfront costs (i.e. solar panels / heat pumps / charging / EV ownership). 

7. What specific challenges or barriers to participation might be faced by particular customer groups?

As noted in IB1’s response to the Department for Science, Innovation, and Technology’s Technology Adoption Review, IB1 noted a key barrier to technology adoption, investment, and participation is a lack of a consistency in vision and policy which is vital for the decision makers in the organisations and companies to de-risk technical and innovation investments. Having a cohesive, consistent vision with clear actions allows for stakeholders to incorporate data sharing and data access at the core of their decisions. 

A robust governance includes having representatives from consumer advocacy/rights groups is essential to ensure any work identifies and collaboratively works through any barriers. IB1 has suggested addressing the following comments on inclusivity in our response to Ofgem’s Consumer Consent Consultation: 

  • Recommend support for other languages (Welsh, other languages used in the UK)
  • Strongly suggest considering how the any solution leads to digital exclusion, and compound exclusion
  • Encourage a measurement of diversity which will be considered with design, including disabilities, excluded from the Equalities Act like dyslexia, or options for text dictation.
8. How can we build and maintain customer trust in an energy smart data scheme? 

Trust and Assurance gives confidence both to people inside companies that they are allowed to share data externally, as well as those externally knowing that they have permission and confidence in what is being supplied.

IB1 supports a robust governance process for the energy sector which is essential to  develop own customer-facing values and business propositions and get them out into the market, anchored on principles of data rights, of machine interoperability and of fair value exchange: reciprocity is at the heart of all of this work. 

In response to Ofgem’s Consumer Consent Solution, IB1 suggested including an element of trust to the design principles. As mentioned in the Data Sharing in a Digital Future consultation, there is a lack of trust in energy companies by consumers. Trust is key for obtaining consent. There may already be ‘trust’ in an entity if there is already an existing contractual relationship with suppliers (rather than introducing a new body).

9. What measures should be considered to ensure customers are protected?

IB1 recommends following the design principles in question 19, and considering how an Open Banking decentralised approach increases reliability through the use of an inherently scalable and resilient technical architecture, and security by eliminating a single big target, which would be attractive for hackers.

Example:

In our response to Ofgem’s Consumer Consent Solution, IB1 proposed how a solution could be modelled on Open Banking:

Each Supplier would provide a consent hub within their existing App and account management website. The implementation of this consent hub would be chosen by the supplier, who are free to develop their own, collaborate on an open source implementation, or buy in a solution managed by one of many software vendors.

When a consumer is asked to provide meter data and consent, the service uses a centrally maintained list of Suppliers, and asks the user to choose their Supplier. Then, using standard protocols in a technical solution using the architectural principles from Open Banking, the service asks the user to authenticate with their Supplier. After the user gives consent, the Supplier returns a token to the service to access meter data. Meter data can be fetched via the Supplier’s service, or direct from Smart DCC using the token created by the Supplier.

When a consumer changes Supplier, a list of consents would be passed to the winning Supplier, who would then give the user the opportunity to give the same consents to maintain their connections to the services they use.

10. What are the potential incentives and barriers for established energy market actors to provide access to customer data (e.g. operational, commercial, legal)? What interventions might be necessary? 

As mentioned in question 1, 2, and 5, incentives, barriers, and benefits should be identified through a robust governance process which can understand, process, and define use cases with relevant stakeholders including incentives and barriers.

As mentioned in IB1’s response to Ofgem’s Consumer Consent consultation, the current methods for obtaining consent and permission from a consumer may be ineffective or inefficient due to:

  • Lack of transparency in obtaining consent – e.g. overly legalistic wording, items hidden in small print, lack of clarity around the full range of partners data will be shared with and/or for what purpose(s).
  • Individual/household dilemma – consent for data sharing pertaining to a multi-occupancy or shared household of people is obtained from a single individual (there may also be a gender bias here if the account holders tend to be male) who may or may not actually live at that address (eg landlord who pays bills) – there is no mechanism to ensure household members are consulted.
  • Revoking or changing consent – it is often easy to give consent (e.g. automatic pop-up) but much harder to change or revoke consent (e.g. requires a log in, hidden in a long settings menu, not available by non-digital means) – this requires much more transparency and an easy process.
  • Lack of trust – as mentioned in the consultation, trust is key for obtaining consent. 
  • Linked services – Lack of understanding about the impacts of giving, changing, or revoking consent for services that may be linked (e.g. reliant on data flows) but potentially operated by different companies. For example, consumers may not understand the impact of rejecting access to 30 minute consumption data on access to smart products and services.

IB1 recommends:

  • A decentralised model, which aligns with the approach taken by Open Banking, and the architectural principles of the Data Sharing Infrastructure for ease of access and protection 
  • A robust governance which allows for collective agreement on standards and legal agreements 
  • Working closely with NPSA and NCSC to ensure their feedback is incorporated.
  • Designing for integration and interoperability with cross-sector data sharing
11. What are the barriers currently faced by third parties in accessing customer data? What potential barriers might be faced by authorised third parties in offering increased or improved services to customers through a Smart Data scheme?

See question 10 for listed barriers and recommendations. 

12. What customer groups should be included in an energy smart data scheme and why? 

No comment. 

13. What aspects of the GB energy mix should be included in an energy smart data scheme and why?

IB1 would also like to understand why any aspects of the GB energy mix may be excluded from an energy smart data scheme. IB1 would recommend this be explored through potential use cases and understanding what is trying to be achieved before excluding any part of the system in the design phase. 

14. What are the potential use cases for an energy smart data scheme? Where relevant, please identify target customer groups or geographic region they would cover.

As mentioned in question 1 and 5, IB1 has identified and documented a wide range of use cases and benefits associated with trusted energy data sharing. Many of them highlight the data sources identified on page 23 of the call for evidence.

Identifying, expanding upon, and prioritising use cases can meet a wider opportunity to transform the energy sector. From IB1’s research, IB1 sees the biggest opportunity for energy data is for strategic planning at national and local level to advance the UK’s industrial and net zero strategies. As part of our research, IB1 have found the need for more granular data, which is very useful for capacity management on the network, load modelling, and flexibility.Choosing the right collaboratively defined key use case can be an opportunity for new jobs and increased system efficiency and resilience.

Identified use cases by data sources (pg 23)

Generation:

A major barrier is around timely and easy data sharing to facilitate predictable planning, understanding current, planned, and required headroom capacity, and to clear the backlog of planning requests to approve more net zero energy sources. 

This includes the need for a trusted way to securely share data, and ensure national infrastructure security. IB1 partnered with SSEN-Transmission, Olsights, Mapstand, SGN, and National Grid on a Strategic Innovation Fund programme REACT to address current planning and future planning for generation siting. See the Discovery Phase report, and the Alpha Phase report.

Data sharing can also be used to better understand how to maintain the assets already in place. IB1, SSEN-Transmission, IBM, and Palantir on a Strategic Innovation Fund programme, NIMBUS, which focussed on granular weather data and network innovation to build for sustainability. See the Discovery Phase report and the Alpha Phase report.

Suppliers:

Through Open Energy IB1 worked with suppliers, a few key barriers identified are understood to be challenges faced by many suppliers, including:

  • Inconsistency of data format, structure and storage 
  • Poor data flow between departments 
  • Data/model duplication because of limited cross-sector collaboration
  • Reluctance to publish incomplete or imperfect data.

Small scale assets:

In our Open Energy Future of heating –  Residential Property Developer use case, IB1 focussed on supporting residential property developers, or consultants operating on their behalf, by facilitating and streamlining access to essential data. For small scale assets, data sharing is needed between DNOs, suppliers, smart meters to understand the demand on headroom capacity 

Properties:

In previous research which touched on individual household properties, IB1 would recommend considering if a selected use case could be solvable through the use of aggregated data rather than individual. The electricity network has physical infrastructure in the Low Voltage feeder (LV feeder) that can be used to aggregate data down to a few households, and provide a simple way to provide highly granular but anonymised data (this is not the case with the gas network, but the gas network can use the same aggregation point when gas and electricity meters are connected together).

IB1 note that smart meters can be found in non-domestic and domestic properties, and Perseus is addressing how a smart data scheme could be implemented to connect green financial loans for SMEs. 

Vehicles

As part of our Open Energy work IB1 have identified, prioritised, and documented two EV use cases. A key aspect is that at least 33% of households do not have a garage or private drive where they could easily charge their own vehicle. This affects lower income households disproportionately, as on-street charging generally has a higher cost than household tariffs, particularly households who also have access to time-in-use (static or dynamic) tariffs that are most suited to EV charging. 

People and communities:

As mentioned in properties, IB1 would recommend considering if a selected use case could be solvable through the use of aggregated data rather than individual.

Local authorities:

As part of our Open Energy programme, it was surfaced that a common challenging issue for Local Authorities implementing their Local Energy Plans is to be able to understand whether or not plans to install these new Low Carbon Technologies would be achievable without Distribution Network reinforcement build being required. See our Local Authority LCT decision making use case (also applicable in vehicle category).

Financial services:

IB1’s flagship programme Perseus will automate access to assurable SME electricity data, so they will be able to see the emissions from their energy use and share it, via reporting solutions, to their banks to unlock green finance (2023 report). This will result in a viable connection between the financial economy and real economy to enable net zero impact in a scalable and assurable manner. When investors have trusted assurable data they are empowered to prioritise investment where needed for maximum net zero impact. 

This has crossover with financing energy efficiency, use of renewable energy,  renewable generation, flexibility services (i.e. solar panel batteries). 

As noted in question 18, there is a risk of unequal access to smart services if we do not address the challenges known to exist in smart meters, known barriers to access, and any other infrastructure collecting the data which will be used in the scheme.

For example, smart metering reporting can be inaccurate, offline, and in 2024 Energy UK confirmed there is a regional divide because of the way meters send usage data back to suppliers. Acknowledging and addressing this will reduce the risk of baking in non-equal access to smart services which arise from a smart data scheme. 

IB1 recognises the focus is on energy data, however, there is a growing potential for a number of use cases with the water industry such as leakage identification and resilience planning. This is also key to understanding the country’s resources, and can aid planning for a number of reasons (hydrogen, CCS, local authority, housing development) and fits into existing regulation and regeneration policies. IB1 recommends working with key regulators such as DEFRA, the Environment Agency, Ofwat, and Ofgem to share existing knowledge and develop best practices. 

15. What datasets should be included in an energy smart data scheme and why? Please consider all types of energy data (e.g. electricity, gas), including which data should be a minimum requirement for any Smart Data use case and which data might be challenging to include.

Part of the use case identification process should include identifying datasets, as seen in our use cases documented in question 14. IB1 strongly recommends following a use case driven approach rather than starting with identified datasets to be released to ensure organisational interest and incentives. IB1 encourages cross-sector collaboration and working on cross-sector use cases (hydrogen, electric vehicles, electrifying public transport, etc). 

16. What opportunities might there be to take advantage of AI and machine learning solutions in an energy smart data scheme? Please consider any additional governance and protections required to mitigate any risks.

As noted in IB1’s response to Ofgem’s AI in the energy sector guidance consultation: 

IB1 encourages cross-sector collaboration and learning wherever possible. IB1 recommends engaging with cross sector (i.e. water, transportation, local authorities, etc) and working with citizen advocacy groups to learn from best practices, ensure guidance is consistent for cross sector use cases (hydrogen, electric vehicles, electrifying public transport, etc), and understands the impact of AI guidance on different socio-economic stakeholder groups.

AI must be designed to mitigate bias and discrimination, ensuring fair access to economic opportunities, financial services, and public resources. IB1 advocates strongly for:

  1. AI governance to integrate with developments in data governance, both within the energy sector and in the cross-economic space (e.g. Smart Data Roadmap, approaches to consent or permission). 

IB1 believes it is important for data governance to establish principles, structures, roles and responsibilities, agreed upon by market participants, that enable auditable, accurate and timely data sharing at a market-wide scale. As mentioned in the IB1’s May 2024 AI consultation response, IB1 recommends that the data ecosystem, and integration with the data governance landscape be acknowledged.

  1. Codifying the relationship and responsibilities of the AI governance landscape in support of the UK’s net zero and climate targets.

IB1 recommends that the developing AI governance landscape codifies a requirement for AI use in the energy sector to demonstrably contribute to the UK’s net zero targets and for this requirement to be open to monitoring and audit. Without codification of this principle there is a risk that AI systems are established to optimise non-environmental goals, while creating negative environmental impacts. 

IB1 acknowledges the risk of AI systems generating increases in energy and water demand. Both the impacts and the demand profile of AI use across the energy system should be subject to scrutiny and appropriately governed to ensure they contribute meaningfully to the UK’s net zero targets.

IB1 notes that in training a model it is highly likely that training datasets will contain sensitive data (it is also possible to use only anonymised data within a training dataset to retain privacy in the model itself), but it is possible to implement techniques where sensitive data is significantly better protected in the training of the model such as aggregation, pseudo-anonymising personal data. A good example of this that has been accepted by Ofgem as appropriate for maintaining privacy is the creation of datasets in energy that aggregate data down to a few households based on which properties are on different Low Voltage Feeders. If there are clear controls on the training data which datasets can and cannot be used to train AI models, then we can expect the produced AI model to be privacy preserving. If you implement data protections after an AI model has already been trained, it is harder to control. If a model has used training datasets with potentially identifiable data within them, the model may provide outputs using this data and can end up linking datasets together to make it personally identifiable. 

17. How should we prioritise different energy use cases? Please consider aspects such as phasing, complexity, data accessibility and participation. 

Use case prioritisation should occur within a governance process with representatives from across the market, therefore, when the data sharing rules are co-designed participants understand the value of engagement, their business case, and the benefit case for sharing data. 

IB1 would recommend starting with use cases focussing around main blockers to transitioning to a net zero energy system. Delivering CP2030 will require reforms to the overarching structures that underpin delivery and operation of the energy system, to ensure they do not act as blockers to deployment of clean power projects. 

As mentioned in question 1, IB1 supports a robust governance process which centres user needs, and makes a business case for the effort of data sharing.

18. What unique or specific features of the energy market (and/or energy data) should we consider when developing a Smart Data scheme?

As noted in IB1’s response to DSIT’s Technology Adoption Review as the data sharing economy develops in a manner which is increasingly fluid and cross-sector, there is an ongoing need for policy and regulatory development which horizon-scans, assesses, and defines responsibility for addressing different aspects of the regulatory landscape. Providing this form of policy and regulatory join-up presents essential support to the incentivising and de-risking of investment in strategic sectors. 

Energy specific features to consider include:

  • The outsized impact electrification has on reaching our net zero goals. 

The Climate Change Committee estimate in the Sixth Carbon Budget report is that transitioning to a clean power system will nearly eliminate the emissions relating to electricity generation by 2050. 

The way the UK generates electricity is increasingly complex and no longer linear. Electricity is being generated across more sites, such as wind and solar farms, as well as by electricity customers generating their own energy such as solar panels on rooftops. Electric vehicle batteries themselves are also a potential place for the storage and re-supply of energy back to the grid, although this does affect battery life.  This means the job of balancing our national grid is increasingly complicated. At the same time, the UK is working towards electrifying  the heating of homes and our transport system (buses, trains, fleet vehicles as well as cars and vans), so not only millions of homes and businesses will use electricity but millions of vehicles too. 

Data sharing is essential to plan for this electricity transition, which involves a lot of work with a wide variety of organisations, in addition to building systems that can continuously automate balancing supply and demand once data sharing is common place. 

  • Complexity and collective agreement across the sector – the energy industry and the organisations who may need energy data is complex and rapidly changing. It can be difficult to meaningfully engage. Cross sector data sharing will bring in more complexities – stressing the importance of robust stakeholder engagement.
  • Cultural change and industry readiness – must interact with the current data sharing culture within the energy companies, and consumers must be engaged to understand their value proposition. 
  • Consumer smart meters: There is a risk of unequal access to smart services if we do not address the challenges known to exist in smart meters. Smart metering reporting can be inaccurate, offline, and in 2024 Energy UK confirmed there is a regional divide because of the way meters send usage data back to suppliers. Acknowledging and addressing this will reduce the risk of baking in non-equal access to smart services which arise from a smart data scheme. 
  • Physical hardware: The energy system consists of long lived physical infrastructure with firmware. As our understanding of security and cybersecurity accelerates over time, we must be aware that not all security concerns can be addressed by downstream software and there are some baked in challenges in using the existing infrastructure. This is a key place where appropriate governance can understand any challenges and collaboratively determine solutions for scheme development.
  • Energy is essential infrastructure: Energy is a fundamental utility and has unique national security considerations. Appropriate engagement with the National Protective Security Agency, and National Cyber Security Centre is required. 
19. What common principles are needed to support the development of an energy smart data scheme and why?

IB1 supports the design principles put forward by the Competition and Markets Authority (CMA) for an effective Smart Data scheme and the Centre for Data Ethics and Innovation (CDEI) suggested key considerations. 

  • IB1 would inquire for more clarity on mandated participation – who does this include? Licensed operators? Third party providers who use energy data? The energy system is complex with many licensed and non-licensed operators and clarity would be appreciated.

Please note IB1’s response to Ofgem’s Governing of a Data Sharing Infrastructure (DSI) Consultation and response to Ofgem’s Consumer Consent Solution.  IB1 urges the alignment of the design principles and governance principles between the Data Sharing Infrastructure (DSI), the consumer consent solution, and an energy smart data scheme. Please find our recommendations to build and maintain trust with core principles below:

  • Governance mechanism is built to function flexibly

As digitalisation of the energy sector, and the wider economy, accelerates it is essential that governance adapts with a shifting technical landscape. There will be a continual balance between addressing user needs and potential threats, necessitating robust governance to be participatory and responsive to a full spectrum of social and environmental considerations shaping the operational landscape, for example including capacity to respond to forthcoming Net Zero 2030 milestones. 

  • Simple and Low Friction 

IB1 recommends a simple and low friction option which builds on previous implementation in other industries, for example Open Banking which has been endorsed by the Competition and Markets Authority (CMA) and the Financial Conduct Authority (FCA), to ensure an energy smart data scheme is aligned with national strategy.

  • Interoperable 

IB1 strongly recommends taking a joined up approach which is interoperable with initiatives across the economy. IB1 suggests the solution defines relationships with adjacent bodies in the energy sector and beyond to enable cross sector interoperability.

  • Agile, Flexible, and Scalable

IB1 suggests introducing a clear process for change management in this principle. As governance needs will likely change with time. This may include indication of how the list of permitted data use purposes will be maintained with additions and removals

  • Transparent and Informative

IB1 strongly recommends that documentation is published openly, along with any accompanying processes, methodologies, financial, legal, operations and governance processes, as also suggested in our DSI consultation response. 

  • Clear and consistent use of definitions and communications surrounding data. IB1 uses the data spectrum to communicate the definitions and differences between Open, Shared, and Closed data. 
  • Inclusive by Design 

The solution intends to protect vulnerable consumers, which can be at odds with requiring technical checks (MFA or similar). IB1 urges the defined user journeys, messaging, terms, and customer support to be easy to use, transparent, and explained in a way that someone with a low technical reading comprehension can engage with. IB1 recommends building on open source, if not incorporated, there is a risk of inadvertently creating a monopoly.

  • Secure by Design

IB1 encourages working with the National Protective Security Authority (NPSA) and National Cyber Security Centre (NCSC). IB1 would also recommend an adversarial analysis to be performed to see where security gaps may occur, and may affect the proposed architecture. The solution must avoid creating large targets for hackers where a compromise affects many consumers. Data required for investment must undergo a thorough assessment of risks, benefits, security measures, and potential international standards as there may be implications for data transfer and use across the UK and international borders. 

  • IB1 recommends a focus on data rights: the same data will be used for many purposes. This means there will be multiple rights, based on purpose, carrying different legal, liability and related conditions. 

IB1 scheme governance is based on five pillars, each of which are essential to development and operation of the scheme:

  1. User needs, materiality, and impact
  2. Technical infrastructure
  3. Data licensing and legal
  4. Engagement and communications
  5. Policy

See more information at https://ib1.org/sops/governance-schemes/ 

20. What are the specific technical considerations for developing an energy smart data scheme? (E.g. data standards, data access, use of APIs, authentication). You are welcome to include visual aids or diagrams to support your response. 

IB1 recommends an energy smart data scheme include the following technical considerations:

  • Taking an open standards-based, transparent, market-wide framework approach to allow for the rapid scalability of secure access to data
  • Reiterating the importance of having governance oversight to avoid anticompetitive practices, and to guard against cartels to ensure it is a fair place to do business
  • Mandating specific technical security standards. These must be agile to respond to changing security requirements and threats.
    • An example is FAPI, which mandates specific security choices with sufficient implementation flexibility to be practical in most environments.
    • Open ID
    • OAuth
  • Using available web standards developers are familiar with to build 
  • Making APIs explainable to machines (i.e. Open API spec when describing an API being registered on the registry – this can generate the code in most languages)
  • Data access. There can be an assumption that the data holder controls data access, and while technically they do, in a scheme they sign up to rules that may require them to release the data. They therefore cannot make ad hoc decisions that give access to a data user (company 1) but not give access to another data user (company 2) who fit the same criteria within the scheme. 
  • Describing data access rules as part of specification for data sharing. Therefore participants can understand on what terms they get the data. IB1 recommends the governance function provides oversight to ensure it is not abused (e.g. anticompetitive practices)
  • Mandatory access control, which should be applied equally (unless otherwise noted)
  • Defining data standards that align with common requirements across schemes, such as for data catalogues, licence representations, permission, assurance or provenance. 
  • Defining metadata standards – and publishing them openly. As mentioned in IB1’s response to Ofgem’s Updates to data best practice guidance, IB1 supported requiring the use of Dublin Core as a Core Standard. IB1 agreed with Ofgem’s recommendation for publishing metadata using the Dublin Core standard, but IB1 also suggested further refining it to specify the Dublin Core-based Data Catalog Vocabulary (DCAT), which is supported by the main data catalogue platforms and is the metadata standard adopted for all EU public sector data publication.
  • Considering how an interoperable identity mechanism may be possible across different schemes. IB1 think this should not be a centralised identity, but a mechanism which can enable cross scheme identity verification. 
  • Building on the work around machine readable licensing terms
  • Developing standards on monitoring, auditing, logging (tools which can look across schemes make sure data is not leaking out of them)
  • Starting with conceptual alignment for interoperability (i.e. data field and protocol alignment) and then moving on to technical alignment
21. What specific privacy and security issues should be considered when developing an energy smart data scheme and how might these issues be addressed?

IB1 recommends the governance process must engage with by SEC, RECCo, Ofgem, NPSA, ICO, NCSC to ensure issues are raised and collaboratively discussed. 

It is essential to consider communications, legal redress, branding, clear use of data, and clarity of permissions. These are just as important as technical security and privacy protection.

Further privacy and security issues to consider:

  • Alignment with personal data protection

In the 2023 Perseus report the technical advisory group preferred to use the word ‘permission’ to ‘consent’. This is because ‘consent’ has a potentially more narrow definition in personal data protection than is necessary for SME data protection. IB1 aligned Perseus as much as possible to the mechanisms required by GDPR and similar data protection legislation.

  • Identifying and agreeing on licensing terms required
  • Data limitation
  • Clarity on what the data is being used for to ensure there is no out of scheme use (minimum sufficient purpose) 
  • A decentralised model, which aligns with the approach taken by Open Banking, and the architectural principles of the Data Sharing Infrastructure for ease of access and protection
  • Clear signalling of membership of a scheme to avoid fraudulent actors 
  • Level of trust in consumer visibility – how it is maintained, and they are kept informed of risk
  • Scheme positions should be auditable and traceable 
22. Which body (or bodies) should be responsible for scheme design and implementation? Which body should be responsible for regulating the scheme? Please include consideration of the most appropriate role for government. 

In collaboration with industry, code bodies and regulators, IB1 has modelled, designed and tested a framework to design and implement Smart Data Schemes using a Trust Framework approach.   

Schemes are co-designed by market participants and implemented using Trust Services. Neither touch the underlying data or anything about the end users.  Trust Frameworks verify that rules have been agreed and can enable their enforcement.

Our approach has three elements:

  1. A mandate to act: the governing body for a sector, whether formal (regulated) or informal (voluntary) acts as the convener to create a mandate to deliver a scheme and implement it. This body can comprise only statutory bodies (e.g. in Open Banking, the FCA and CMA), only commercial bodies (e.g. STREAM), or a blend (e.g. Perseus). 
  2. Co-design of Schemes: a collaborative process to discover and co-design the rules. This includes five areas: purpose, technical, legal, communications and policy. Once rules are established, processes for change and ongoing governance are codified and maintained. 
  3. Scheme implementation using Trust Framework: this is done in a machine-compatible and enforceable manner

In assessing where governance is approached separately/collectively, IB1 proposes a governance body (and any subcontracted entities), would find it helpful to consider the following (non-exhaustive) factors such as:

  • Goals/aims: How are goals defined and set? Who is involved? How is the balance of goals assessed across technical, socio-economic, and environmental domains? Is there potential for goal conflict across the different nodes and, if so, how will this be managed?
  • Coordination: how will the governing body coordinate with developments within and beyond the energy sector? How will this feed into goals, design choices, and definition of technical/architectural parameters? How might this need to evolve over time?
  • Roles and responsibilities: How are roles and responsibilities defined? Do these differ across each node or are the same roles/responsibilities universal? 
  • Change management: How will change management processes work across the schemes? Are there different stakeholder or technical requirements for separate processes? Are different stakeholders (i.e. with different roles or areas of expertise) required to co-construct and/or sign off changes to different parts? 
  • Communications: If different stakeholders are involved how are these stakeholders engaged and communicated with? Do they have different communication needs that must be built into governance processes or cadences?

As mentioned in our response to Ofgem’s DSI governance consultation, IB1 suggests that Open Energy be formally considered as a vehicle for the governance and implementation of the Trust Framework. Open Energy, funded by public money and coordinated by the non-profit body Icebreaker One, has been specifically developed for this purpose using a combination of radically transparent methods of open working, extensive consultation with stakeholders, and the input of specific domain expertise from energy industry, academic, and Smart Data specialists. IB1 has been involved in the DSI as the governance advisory partner, and is involved in the MVP through inputting into the pilot development, and use case exploration.

Our work to date provides strong justification that the structural model of Trust Frameworks and Schemes initially developed through Open Energy and subsequently advanced through IB1’s programmes such as Perseus and Stream. 

23. What are the required roles and responsibilities for the ongoing operation of an energy smart data scheme? This might include (but is not limited to): accreditation, accountability, oversight, enhancement and liability. 

As noted in IB1’s response to Ofgem’s DSI governance consultation, IB1 suggests there is clear guidance as to how rules are established, overseen, enforced, and changed. These must be explicit and transparently codified roles of the governance body and must also detail under what circumstances any of these roles can be delegated and/or subcontracted to specialists. 

Accordingly, IB1 recommends that the roles include definition of processes and/or rules for the establishment, oversight, enforcement, and change of: Stakeholder mapping, engagement and representation, goal setting, defining success criteria (across technical, socio-economic, and environmental domains), monitoring, reporting, and verification (MRV), change management, communications, dispute resolution, liability and redress, any formal responsibilities towards meeting cross-economy policy goals such as: Net zero, Industrial strategy, social policy.

IB1 further recommends that roles are included to oversee – where not already covered by another body in the broader environment – the definition of processes and/or rules for the establishment, oversight, enforcement, and change of: data rights, adjacent agreements (e.g. membership contracts / terms of use), guidelines (e.g. antitrust, fairness, transparency, publishing).

Finally, IB1 suggests that the governance body should have an active and transparent role in defining formal and informal relationships with adjacent bodies in the energy sector and beyond. This role may include jointly establishing and maintaining:

  • Channels of communication 
  • Obligations on reporting or information sharing
  • Formal processes and roles for engagement (e.g. assignation of ‘observer status’ in certain governance fora)
  • Approaches to sharing and/or allocating roles when approaching shared issues 
  • Appropriate accountability structures
  • Approaches to reduce forum proliferation (and ensuring associated fair access to governance fora for smaller organisations with less resource)
  • Approaches to contributing or responding to cross-sectoral policy and regulatory developments in a joined up manner.

The suggested role changes above imply a set of associated responsibilities which are outlined in the sub-bullets. Many of these responsibilities are likely to constitute oversight rather than design/delivery, allowing for subcontracting arrangements to take place where required. IB1 suggest that a governance body holds responsibilities for the oversight of:

  • User needs identification, testing, and convening
  • Assessing and measuring impact across socio-economic, environmental, and technical domains
  • Where impacts are undesirable, performing impact mitigation 
  • Ensuring cohesion (of procedural, legal, technical approaches)

Implicit across all our suggestions is the principle that key roles and responsibilities explicitly include reference to the wider socio-technical landscape. IB1 suggests that codifying these responsibilities would provide an improved balance between technical, social, and operational elements of governance. While not all areas of responsibility need to be undertaken directly by the proposed governance body (e.g. it may be possible to subcontract an appropriate body to support stakeholder engagement) IB1 strongly suggest that the following (non-exhaustive) points would benefit from more formalised oversight, governance integration, and appropriate resourcing : 

  • Data rights and surrounding legal structures governing the exchange of data and associated intellectual property
  • Stakeholder engagement and communications
  • Cross-sector, policy and regulatory input/coordination (including social, economic, and environmental factors)
24. What common functions and responsibilities should be centralised to enable interoperability with other markets outside the energy sector?

A core centralised capability must be the design principles. Additionally, IB1 recommends governance as a centralised space to identify and discuss considerations and adoptions.  

The governance process should collaboratively agree upon:

  • Licence compatibility 
  • The intent to work toward interoperability and working in widely understood formats. 
  • Adoption of common web standards as the default (unless insufficient) to allow for widest possible number of technologists understand 
  • The use of consistent tooling which is well understood by stakeholders.
  • Choosing security standards 
  • The use of open source
  • Conceptual alignment on what metadata means (better yet  – technical compatibility), and aligning around standards. 

To enable interoperability, IB1 recommends considering how an interoperable identity mechanism may be possible across different schemes. IB1 think this should not be a centralised identity, but a mechanism which can enable cross scheme identity verification. This is a key area of research with further needed around how a federated identity system may work. 

25. What are your views on the feasibility to deliver an energy smart data scheme? Please consider any current or planned industry developments or changes that might affect delivery and highlight any key challenges.

Perseus

It is feasible to deliver an energy smart data scheme, IB1 are running the Perseus programme (https://ib1.org/perseus/) with a core use case focusing on the sharing of 30-minute electricity consumption data, which is combined with corresponding 30-minute local grid carbon intensity readings to calculate assurable monthly greenhouse gas emissions. 

As mentioned above, IB1 are following a robust governance process https://ib1.org/sops/governance-schemes/ and have brought together over 150+ organisations to co-design the programme (see 2024 report here: https://ib1.org/perseus/2024-report/). Perseus is now in its pilot phase,  involving real data sharing and real loan-making. 

It has been designed to scale internationally: 

  • With global members that already do business with millions of SMEs, including Lloyds, Barclays, NatWest, Tide, Sage, Xero and Intuit
  • With a Scheme agreement that is extensible to other domains, adaptable to different legal jurisdictions and sectoral data regimes, and compatible with GDPR

Our core recommendation to ensure an energy smart data scheme is feasible is to ensure governance is up and running from the start. 

26. What challenges and risks should we consider when developing an energy smart data scheme and how can we mitigate these? This might include (but is not limited to): competition; customer exclusion; data quality or data misuse; ethical, operational or technical concerns

As mentioned throughout the consultation, a non-exhaustive list of challenges and risks include:

  • Developing a centralised solution. 
    • Mitigation: embrace a decentralised model, which aligns with the approach taken by Open Banking, and the architectural principles of the Data Sharing Infrastructure for ease of access and protection (ensures alignment with national strategy, Open Banking has been endorsed by the Competition and Markets Authority (CMA) and the Financial Conduct Authority (FCA))
  • Not codifying the relationship and responsibilities of the energy smart data scheme to be in support of the UK’s net zero and climate targets. This is essential to meeting the UK’s net zero and industrial strategy goals.
    • Mitigation: Codify the relationship between an energy smart data scheme and existing net zero goals
  • Not following a use case driven approach. The risk is trying to do too much at one time, and the programme becomes overwhelmed without a core focus point.
    • Mitigation: follow a use case driven approach – see question 1 for benefits of taking a use case driven approach. 
  • A chosen use case does not have a clear business impact case. If there is no financial incentive, there will be no movement.
    • Mitigation: an advisory group articulates their business case for the chosen use case. 
  • Failure to implement governance from the start, and governance failure to address broader user needs, technical implementation, legal, communication / engagement and policy impacts.
    • Mitigation: robust governance from the outset. 
  • Lack of cross sector collaboration. Risk of non-interoperability and not taking the learnings from other sectors.
    • Mitigation: actively engage with stakeholders from the start
  • Too much emphasis on a technical solution  – must equally address governance, user needs, business, social, legal, engagement and communications to be successfully implemented and ensure a scheme is fit for purpose
    • Mitigation: understand the holistic approach required – user needs, legal, policy, and communications
  • Cultural change and industry readiness 
    • Mitigation: interact with the current data sharing culture within the energy companies, and consumers must be engaged to understand their value proposition. 
  • Stakeholder engagement for collective agreement across the sector
    • Mitigation: engage early, often, and formally through governance
  • A scheme is seen as a technical solution rather than a holistic solution.
    • Mitigation: a trust framework incorporates technical, communications, engagement, legal and ongoing governance arrangements.
  • Unequal access to smart services if we do not address the challenges known to exist in smart meters, known barriers to access, and any other infrastructure collecting the data which will be used in the scheme. This unequal access will be baked into any smart services offered and may unintentionally miss out key beneficiaries.
    •  Mitigation: robust governance experience to reduce unintended impacts
  • Creating unintended monopolies, negative incentives, corporate capture, and data misuse
    • Mitigation: robust governance, embracing and building upon open source solutions. 
27. What are the potential implementation costs to industry of introducing an energy smart data scheme? What aspects of a scheme might be most challenging to implement? 

Implementation costs will include secretariat functions for a governance body, energy company time for stakeholder engagement and scoping requirements, and technical implementation. This will include team members from across an organisation, which may include innovation, technical, data, research, legal, communications/PR, and policy compliance teams. 

Identifying the user(s), their needs and developing use cases requires time, effort and resource. This can be a challenging aspect of a scheme to define but it is a core element as everything is built around the user needs. 

28. How might implementation and ongoing management costs of a scheme be distributed across industry participants in an energy smart data scheme? 

IB1 is co-funded using a blended membership and grant model, which helps accelerate market development, adoption and carry out  neutral research. This is based on the  success of Open Banking and the Open Data Institute. 

In Phase 3 of Open Energy, IB1 formed an advisory group focussed on Membership. The group settled on a membership model to be a financially independent service that will not require government funding in the long-term and will support the needs of both industry and government policy. Membership was categorised by aggregate turnover or non-profit status. User needs for data sharing in the energy sector tend to differ by type of organisation. Our analysis identified common user needs across our five membership categories: 

  • Strategic partners – regulated entities with an obligation to share data
  • Enterprises – companies with aggregate annual turnover of at least £36m
  • SMEs – companies with aggregate annual turnovers between £1.7m – £36m
  • Micro-businesses – companies with aggregate annual turnovers under £1.7m
  • Non-profits – including trade bodies, public sector, universities, charities, community energy etc. where specific rules and features apply
29. Do you have any additional comments on any aspect of developing an energy smart data scheme that has not been covered elsewhere in this call for evidence?

Of concern is that there is material referring to “domestic consumers” when the Data Bill addresses both business and consumers as users. There is also an over-emphasis on consumption data and not broader whole-systems data (e.g. that will support flex, demand response, etc ), and care should be taken over language (e.g. ‘consent’ vs ‘permission’).

IB1 notes a few key aspects not covered in the call for evidence:

  • Recognition of the legal agreements, liabilities, redress, and assurance.
  • We strongly advocate for adding in a requirement for work around stakeholder engagement and communications to convey why stakeholders should trust in the process, system, and data sharing in addition to why people should be engaged with it or not.
  • More detail about monitoring, delivery oversight, complaints, and how this scheme would engage with policy would be appreciated. 
  • More detail on the review process for involving national infrastructure departments
  • Our data infrastructure incorporates many categories of data that have varied levels of sensitivity. In order to handle this complexity, and to ensure data is appropriately protected IB1 have developed a system of data sensitivity classifications https://ib1.org/data-sensitivity-classes/ 

See all referenced IB1 response documents here: