To unlock new capacity for electric vehicle chargers and heat pumps, UK Power Networks (UKPN) is turning to a £2m machine-learning tool to create a Matrix-like simulation of the electricity network.
The ‘Envision project’ could release almost 70MW of capacity by 2028 without physically upgrading the network, according to UKPN, saving up to £4m over the five-year period.
The machine learning tool simulates the flow of electricity through UKPN’s networks, building new predictive models that combine UKPN’s data with external and real-time data from monitoring devices connected to substations.
The machine-learning algorithm then creates a simulation of the electrical load in specific areas and expands it across the entire network, with engineers then comparing the simulation to real life physical monitors.
This feeds the software more and better data over time, so the algorithm gets more accurate.
UKPN is collaborating with CKDelta on the new Envision project, which is set to run till August 2022.
Ian Cameron, head of Customer Services and Innovation at UK Power Networks, said: “Our customers rightly expect us to do everything we can to make the switch to electric cars and low carbon heating as affordable as possible.
“Through Envision, we’re thinking outside the box and re-imagining traditional ways of working, to make it happen.”
Simone Torino, head of Product and Business Development at CKDelta, said: “In a world where the uptake of new distributed energy resources and the increasing electrification of transport are impacting electrical demand and distribution network constraints like never before, having this type of modelling and predictive analytics capabilities is a game changer for the utilities sector and has potential to reshape how we approach demand and supply in other sectors such as transport.”
Image: UKPN
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