AI Generative Design Tool for Low-Cost District Heating Networks (Phase 2)

Our project objective is to build a generative design tool that will automate the optimal design of district heat energy networks. Currently, design is costly and time-consuming and often lacks sufficiently detailed data to ensure system efficiency. In many cases this leads to over-sizing of equipment which increases capital costs which are ultimately passed on to the end consumer or can make projects unviable.

By developing a new, cutting-edge, generative design tool our project will accelerate district heat deployment, and enable the UK to meet its 2050 vision of 20% of heating demand being met by heat networks.

1) Using an automated, computer-driven process, we will radically reduce the up-front costs of modelling and system sizing;

2) Using the latest AI techniques combined with detailed geographic data we will optimise system design to increase the affordability of heat networks and maximise their viability.

Our solution will radically reduce the cost of district heat and improve its viability. End consumers will benefit through lower heating costs, warmer homes/buildings and reduced fuel poverty. Taking into account multiple design options will allow for greater focus on zero-carbon fuel sources (including hydrogen) which will promote a new generation of true zero-carbon district heat. End users that stand to benefit include Local Authorities, Major Heat Users, Social Landlords, and suppliers of Heat. Direct users that will benefit from improved productivity and accuracy include Engineering Consultancies, Local Authorities, Network Operators and Suppliers/manufacturers.