To unlock new capacity for rapid EV chargers, UK Power Networks is turning to a £2 million machine learning tool to create a Matrix-like simulation of the electricity network.
Dubbed the Enivison project, UK Power Networks is simulating how power is flowing through its networks across London, the South and South East of England, giving the company better visibility as to how its network is performing. The DNO notes that with this added visibility, it could potentially unlock additional energy capacity equivalent to 1,371 new rapid electric car chargers by 2028.
Experts forecast Envision could release almost 70MW of electricity capacity by 2028, creating more space for EV chargers or low carbon heat pumps. This means engineers won’t need to physically upgrade the network to release capacity, leading to significant cost and time savings: up to £4 million in total over the next five years.
However, UK Power Networks appears to be taking both approaches – both using machine learning to enable low-cost energy capacity increases, as well as upgrading its network for a net zero future. The firm has announced a £4.5 billion plan that will see its network decarbonised.
While UK Power Networks is making room for more EV chargers, the company’s network already has more chargers connected to it than any other. In fact, over the past 12 months, it has seen connections of new EV chargers rise by 42%.
Envision is building new predictive models which combine UK Power Networks’ data with external and real-time data from monitoring devices connected to substations. The machine learning algorithm will create a simulation of the electrical ‘load’ in specific areas and expand it across the entire network. Engineers will compare the simulation to real life physical monitors; feeding the software more and better data over time so the algorithm gets more accurate
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, which is collaborating on the project, added, “The aim of the Envision model is to generate a ‘virtual sensing network’ that uses advanced data capabilities and machine learning to simulate the behaviour of the network at scale, accurately estimating changing network load profiles. 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.”
