Synthetic Data for Research and Innovation
What are the challenges?
Access to high-quality data is essential for energy system research and innovation. However, organisations often face challenges such as limited data availability, incomplete datasets, and restrictions caused by privacy, commercial sensitivity, or safeguarding requirements. Some challenges are:
Data gaps
Limited or incomplete datasets can make research difficult.
Privacy Concerns
Data often contains sensitive information that requires protection.
Commercial sensitivity
Organisations may be unable to share data due to commercial restrictions.
Coverage limitations
Datasets may not represent all locations, communities, or technologies.
Stakeholder challenges
Issues identified through SENSE engagement activities and webinars.
Synthetic data as a solution
Synthetic data is artificially generated data that aims to preserve the characteristics and patterns of real-world datasets while protecting sensitive information. It can help researchers explore scenarios, test models and develop new tools when access to real data is restricted.
The benefits of synthetic data?
Preserves privacy
Enables wider sharing
Fills data gaps
Supports AI and modelling
Creates data for locations where real data is unavailable
What we did in SENSE
As part of SENSE, we explored how synthetic data can help make valuable energy-related datasets more accessible while preserving privacy and supporting innovation.
1. Public EV Charging Data
THE CHALLENGE
Real-world EV charging data was available for only a limited number of regions, including Scotland and Solihull. This restricted the ability to explore charging behaviours across different locations and demographic groups.
WHAT WE DID
We developed a synthetic EV charging dataset designed to capture realistic charging patterns and extend the usefulness of the original data. It supports exploration of a wider range of locations, user types and charging behaviours.
KEY OUTPUTS
1. Synthetic EV charging dataset
2. Synthetic data generation tool
3. Example datasets for research and testing
4. Generation of charging profiles for different locations and demographics
THE IMPACT
Researchers and innovators can explore EV charging behaviours, develop models and test solutions without needing direct access to the original location-specific data.
2. Hospital Energy Data
THE CHALLENGE
Hospital energy and operational datasets can contain safeguarded information, limiting opportunities for data sharing, analysis and innovation.
WHAT WE DID
We developed synthetic hospital datasets designed to preserve important characteristics of the original data while helping protect sensitive information. These datasets can also support the creation of representative data for hospital sites where real-world data is unavailable.
KEY OUTPUTS
1. Synthetic hospital dataset
2. Dataset generation capability
3. Example datasets for analysis and testing
4. Generation of data for additional hospital sites and scenarios
THE IMPACT
Researchers can work with realistic datasets for analysis, modelling and innovation without requiring direct access to the safeguarded source data used during development.
Why It Matters
Synthetic data can help unlock new opportunities for research and innovation by making high-quality datasets more accessible.
Through SENSE, synthetic data is helping researchers, innovators and organisations:
Explore energy system challenges more effectively
Develop and test new tools and services
Reduce barriers to data access
Protect privacy and commercially sensitive information
Create representative datasets for future scenarios and locations where real data may not yet exist
By combining domain expertise with advanced data generation techniques, synthetic data can support innovation while maintaining trust and responsible data stewardship.
Resources
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Learn more about synthetic data and its applications through our webinar:
Introduction to Synthetic Data Webinar (ADD LINK)
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Explore the synthetic EV charging dataset developed through SENSE:
Synthetic EV Charging Sessions (ADD LINK)
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Generate new synthetic EV charging scenarios based on your requirements:
SENSE Synthetic Data Tool (ADD LINK)
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A synthetic hospital dataset is also available through SENSE. Access may require registration or approval due to the nature of the underlying project.
(ADD DATASET LINK)
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Further details of the methodology and findings will be available in an upcoming research publication.
Paper link to be added following review. (ADD LINK)
Get Involved
We are continuing to explore new applications of synthetic data across the energy system.
Whether you are a researcher, data scientist, technology developer or domain expert, we welcome collaboration and feedback.
Interested in learning more or contributing to future synthetic data activities?
Contact the SENSE team at: sense@es.catapult.org.uk