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.
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
