Q-REALM Wind

Q-REALM Wind is a feasibility study being undertaken by EY and ORCA Computing, together with critical input from a multi-national energy producer to explore the potential of using generative modelling techniques on ORCA's PT-Series photonic quantum processor for onshore and offshore wind farm location optimisation. The objective of the project is to assess the impact of novel algorithms that use data science and quantum computing (vs traditional techniques) to optimise the placement of wind turbines for maximum energy output and cost efficiency, while considering various environmental and regulatory considerations.

The project is particularly timely because of the imperative to improve the UK's energy security while simultaneously helping more organisations achieve net-zero. The project aims to show that more efficient use can be made of the nation's resources, thus delivering a better return on the investment in renewables, as well as improving the stability and reliability of wind power to minimise power transmission loss and reduce dependencies on fossil-fuel backup. The project also encourages further innovation within the renewables industry by showcasing the potential for quantum computing to be used in other parts of the supply chain -- from more efficient turbine design to reliable operation over the long lives of these assets. In addition, this project will help to demonstrate the feasibility of near-term quantum computing applications and encourage more organisations to start their journey to quantum readiness.

The project also builds on EY's broad base of research and thought leadership in quantum computing and AI, allowing the project team to explore quantum readiness in a hands-on fashion, while bringing to bear EY's & ORCA's breadth and depth in AI, data science, and the energy domain.