Edinburgh University spin-out, Enian, has secured a £500,000 Innovate UK grant to develop a new cost-predicting algorithm that could boost the uptake of renewable energy sources across the UK.
The deal will see the renewable energy software developer collaborate with the University of Edinburgh’s School of Engineering – as well as The Data Lab – over the next 19 months to develop and test the cost-of-interaction prediction algorithm.
The project is set to launch in early December and will run until May 2022.
Researchers said the project will accelerate the development of a system aimed at digitising, automating and enhancing the way project planners estimate the cost of connecting a new power plant, for example, to the nearest available grid.
At present, grid connection costs are among the most difficult to predict but account for a significant share of the total costs for generating new power.
Grid owners and operators are increasingly adapting to a more flexible energy mix to accommodate more renewable energy sources.
As such, they need to be able to provide rapid, data-driven estimates to project managers to give them confidence in their decision-making, improve cost efficiency and strengthen the resilience of the energy system from a planning point of view.
Phillip Bruner, CEO of Enian, said: “The highly variable but also significant costs of interconnection are some of the most critical to understand from an early stage.
“We’ve done a lot of research on what causes commercial solar and wind power plants to fail.”
Bruner added: “It’s often the case that developers get caught off guard by grid constraints or runaway costs. Thanks to Innovate UK, with machine learning and open access data, we can unlock a new cost-saving capability for the UK energy sector that will help accelerate the path to net-zero.”
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Daniel Friedrich from the University of Edinburgh School of Engineering commented: “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.
“This transition requires a massive increase in distributed renewable generation which needs to be fed into the grid and transported to the demand centres. We will use our expertise in network power flow models, geographic information-based systems and data-driven algorithms to streamline this process and to help unlock the full potential of the renewable energy sector in the UK.”
Gillian Docherty, CEO at The Data Lab commented: “Never before has it been more pertinent for data-informed solutions to be brought to the energy market.
“With the ever-increasing need for energy supply as global populations rise, it is incredibly important that we scale our supplies in a clean and clever way, leveraging cutting edge data science to guide our approach.”