British universities turn to AI to improve energy efficiency
Universities across Britain are to start employing artificial intelligence in a bid to cut energy costs in buildings by as much as 30 per cent
Universities in the UK are to pilot the utilisation of artificial intelligence (AI) as they look to improve energy efficiency. The scheme – involving Anglia Ruskin, Bath, Bristol, Newcastle, Regents and York universities – is being facilitated by The Energy Consortium (TEC), a contracting authority with many university members, and will mine smart-meter data using AI to identify energy waste, improve efficiency and cut costs.
The project, in partnership with AMR-DNA, an Energy Assets service, will use underlying AI software developed by kWIQly. It will interrogate huge volumes of energy consumption data, covering many hundreds of buildings, to identify opportunities to improve energy efficiency.
TEC is running the trial for its university members through its Flexible Gas Framework and will be collaborating with estate management teams to evaluate the results.
Steve Creighton, Head of Member Services at TEC explained: “Consumption reflects when a plant operates. Activity can be reverse engineered from consumption, allowing AI to search, quantify and prioritise. This in turn makes it possible to manage problems on a daily basis for even the largest estates. As time-to-action is critical in reducing waste, early identification and diagnosis enables financial gains and carbon reduction for our members.”
“As technology enables, and as climate-change really starts to bite, we must deliver solutions suited to overlooked and complex energy issues.’
Continuous estate oversight has the potential to expose significant opportunities for improving energy efficiency (cutting energy costs and CO2), and AMR-DNA’s AI enables the rapid identification and resolution of problems.
Stewart Love, Group Commercial Director for Energy Assets, understands why significant multi-site portfolios have, until now, been less interesting to suppliers of software solutions. He said: “99.8 % of companies rely on data from under 20 meters, corresponding to one or perhaps a handful of buildings where local problems are obvious and relatively easy to examine. However, universities, supermarkets, high-street retail chains, pubs, banks and local government fall in the remaining 0.02% that have far more complex and dispersed challenges.”
James Ferguson, CEO of kWIQly, said: “As technology enables, and as climate-change really starts to bite, we must deliver solutions suited to overlooked and complex energy issues where so much goes unmanaged. If an energy manager can reduce energy spend by 30% or more in single buildings without major investment, then it is essential that waste is identified and savings are tracked automatically at scale. Simply put, this allows their energy management expertise to be greatly amplified.”