Following a pilot project to improve wind farm efficiency, Natural Power has been awarded more than £100,000 from Innovate UK, the UK’s innovation agency, to further develop its research into ‘Combining complex and disparate data sources to define and deploy leaner and smarter operational strategies to improve the performance of wind farms’.
As wind power generation enters a new era in subsidy-free markets, there is a growing need to maximise the efficiency, lifetime and availability of wind turbines, while minimising operating costs. Adopting a data-driven approach to this is essential.
Leanne Ramage at Natural Power, said: “The outputs from this project will put Natural Power at the forefront of wind turbine analysis services, but will also significantly extend the range of maintenance planning and delivery offered by our site management teams. The increase in capacity will enable us to offer turbine management that is leaner and smarter, contributing to the key drivers of increasing efficiency, availability and turbine lifetime while reducing overall operating costs.”
Natural Power has a strong track record of gathering and analysing data generated from wind turbines and additional sources, including first of a kind deployment of nacelle mounted lidars.
There are already products available that aim to improve turbine performance through analytics, however, these products are generally focussed on one aspect of the data, for example, CMS data for turbine component health checks.
Ramage continued: “Natural Power is in a unique position where we have analysis, asset management and independent servicing expertise all interlinked, and provide wind farm management to approximately 30% of the UK wind farms. This project will develop a model that takes account of the full range of data available – from handwritten anecdotes to high-resolution SCADA data – and capitalises on our wealth of hands-on experience of the practical management and servicing of wind turbines.”
As part of this project, Natural Power will collaborate with the Science and Technology Facility Council and tap in to its data science expertise to help bring this new product to fruition. The project is due to kick off on 1st October 2019.
