Veolia uses AI to optimise Sheffield heat network

AI is being used for the first time to increase heat delivery and optimise efficiency on one of the UK’s largest and oldest district energy schemes.

Network operator Veolia is using the AI tool on behalf of Sheffield City Council for Sheffield’s District Energy Network, applying data-driven thermo-hydraulic modelling to optimise temperature and network pressure over the 44km-long network.

By taking real time data from across the network, including data collection from the individual heat meters that serve connected buildings, and predicting heat demand and weather patterns,  the system is set to reduce peak loads by up to 20%  and increase the heat delivery capability by 25%, Veolia says.

The network has been operating since 1988, supplying heat from household waste at the Sheffield Energy Recovery Facility to over 125 commercial and public sector buildings including the Lyceum Theatre, Sheffield City Hall, Weston Park Hospital, the Universities and the Millennium Galleries.

Over 50% of the heat qualifies as renewable under the Renewable Energy Guarantees of Origin (REGO) scheme.

The AI software takes data inputs from sensors across the network and combines this with external data to calculate potential heat losses in underground pipe sections, plantroom pipework and energy centres and then optimises the energy consumption of the buildings. Veolia says this allows common problems such as hydronic bottlenecks to be avoided, which limits any potentially disruptive and costly retrofits on the underground heat networks and improves fault tolerance and estimation of energy consumption.

Donald Macphail, the company’s Chief Operating Officer – Treatment, said:

In the UK, almost half of the final energy consumed is used as heat, and the domestic, commercial and public sectors account for two-thirds of this consumption for space heating and water heating . As we move to reduce climate impact we need to decarbonise these important heat requirements.