A collaboration between the School of Engineering, University spin-out ENIAN and the Data Lab will revolutionise the way renewables projects predict grid connection costs.

The Innovate UK grant worth half a million pounds will develop a cost-of-interaction prediction algorithm to allow wind and solar developers to assess the cost of grid connection at an early stage and avoid planning pitfalls.

Cutting-edge big data and machine learning will leverage expertise in power-flow models and geographical information systems to create certainty in renewable projects and drive the transition to net-zero.

"We've done a lot of research on what causes commercial solar and wind power plants to fail", said Phillip Bruner, chief executive of ENIAN. "The algorithm will help project managers to estimate previously unexpected grid connection costs."

"We're excited to continue the successful collaboration with ENIAN in this cutting-edge Innovate UK funded project which can make a real difference for the drive to net zero", said Dr Daniel Friedrich of the School of Engineering, University of Edinburgh.