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SENSE data in action:
Synthetic data for EV charging and beyond
Join us in our upcoming webinar to explore how synthetic data can support energy research and innovation
What you'll learn
- How SENSE-Synth creates realistic synthetic EV charging sessions
- How charger type and location shape the data it generates
- How charging behaviours are modelled across energy use, duration, rate and timing
- How the model produces useful data without identifying individual sites
- How it performs on both existing and previously unseen chargepoint sites
- Where its limitations lie and how the data could support real-world decisions
About
the webinar
How can researchers and innovators access useful EV charging data when commercial sensitivity and privacy keep much of it out of reach?
Join Energy Systems Catapult, SENSE and CountingLab for the first in a new webinar series exploring the data and research connected to the SENSE platform.
CountingLab will introduce SENSE-Synth, a generative model that creates realistic, non-identifying EV charging sessions based on charger type and location. The model has been developed using around 5.4 million real charging sessions from the public ChargePlace Scotland network.
You’ll discover how SENSE-Synth identifies different charging behaviours across energy use, duration, charging rate and timing. The session will demonstrate how a soft-membership classifier matches a site’s location with a library of plausible charging patterns. This means an unfamiliar location can be modelled using a blend of relevant patterns, rather than being forced into a single category - helping the output remain non-identifying.
You’ll also see how the model performs on both existing and previously unseen chargepoint sites, where its limits lie and how synthetic data could support network planning, charge-point siting and tariff design.
Our
Speakers
Dr Daniel Dimanov
Principal Data Scientist, CountingLab
Dr Daniel Dimanov is a Principal Data Scientist at CountingLab Limited with experience in AI and data science since 2018. His work covers machine learning, computer vision, predictive modelling, generative AI and large-scale data analysis across the energy, retail and defence sectors. As part of the SENSE collaboration between CountingLab and the Energy Systems Catapult, he has been working on synthetic EV charging session generation.
Dr Colin Singleton
Technical Director, CountingLab
Dr Colin Singleton is Technical Director at CouuntingLab Limited, a pioneering company in the field of AI and Data Science.
Dr Singleton has 25 years experience working with data science and analysis including forecasting, clustering, statistical modelling, uncertainty estimation, anomaly detection and generative AI. He won the original Global Energy Forecasting Competition for electricity demand back in 2014, was a significant part of the Thames Valley Vision project that refined techniques for modelling energy consumption, has led InnovateUK projects for fusing energy data with public data sources, and a huge variety of analysis all sorts of data from different sectors including imagery data, time series, shopping transactions, customer profiles, etc.
Turn limited data into better decisions
Explore how realistic synthetic EV charging data could support network planning, charge-point siting, tariff design and the development of new research and solutions.
This webinar is facilitated by
Delivered in partnership with
