Advanced AI for Integrated Financial Optimization of Wind Energy Assets

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REOptimize Systems (REOS), was formed to exploit research developed at University of Edinburgh, which has implemented a unique approach to increasing the efficiency of wind turbines. Through advanced modelling and the application of novel machine learning techniques the algorithms minimise the end-to-end losses in the system. This technique has patents pending and is the result of 7 years of research at The University of Edinburgh. The success of the algorithms has been proven experimentally in small-scale wind turbines, and found to yield increases in energy capture of 6%. A 6% increase in energy capture can drive net profit increases for the operator on the order of 50%-100% depending on the specific turbine and location. If only half of UK turbines achieved a 6% gain, it would result in an additional 3000 GWhr of generation and a saving of 1.3 million tonnes of carbon in a single year. This is equivalent to removing around 290,000 petrol passenger cars from the streets. However, this 6% gain has been proven only in medium-scale wind at approximately 100 kW ratings. It is expected that larger turbines will start from a position of better control which will allow us to achieve gains on the order of 3%. REOS is currently preparing a pilot project to validate the technique on a MW scale Siemens 2.3-92 turbine, which is a workhorse of the UK onshore fleet. Now, through this new project, REOS will develop and integrate novel machine learning technologies into a single platform which will provide end-to-end financial optimization of wind power assets, with a truly holistic view of the entire wind system. The project will develop and integrate: * Continuous per-turbine settings optimization * Advanced detection of false alarms to increase in-service time * Advanced AI-based wind farm control This will create a step-change in the control and performance of wind energy assets with the aim of maintaining the gain of 6% increase in energy output in large modern wind farms. This will contribute to creating sustainable innovation and help deliver the transition to net-zero.