ENIAN to build renewable uptake with algorithm

ENIAN has this week been awarded a £500,000 Smart Grant by Innovate UK to develop a new cost predicting algorithm set to accelerate the uptake of renewable energy across the country.

The company, a spin-out of the University of Edinburgh School of Geosciences and the Department of Electrical & Electronic Engineering at Imperial College London, will collaborate with the University of Edinburgh School of Engineering and The Data Lab over 19 months to develop and test the cost-of-interconnection prediction algorithm (CIPA), with the aim to digitise, automate and enhance the way that project planners estimate the cost of connecting a new power plant to the nearest available grid.

Currently grid connection costs are some of the most difficult to predict but make up a significant share of the total costs for generating new power. However grid owners and operators must adapt to a more flexible energy mix to accommodate more renewable energy sources, so 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. 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.”

The project will start in early December and will run until May 2022

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