With tough offshore conditions in the North Sea taking its toll on the condition of turbines, a large percentage of lifetime outgoings for offshore wind farms are associated with maintenance.
The RGU team, including Head of the School of Engineering Professor John Steel and PhD student Yashwant Sinha, is focused on developing a tool which would ensure that companies were able to carry out turbine maintenance and sparesholding in the most efficient manner.
By inputting specific information generated by an offshore windfarm into the tool, it would then automatically generate an optimal maintenance programme and critical sparesholding inventory tailored to those turbines.
This would minimise the direct costs of maintaining the wind farm and maximise the availability and reliability of offshore wind farms and associated grid connections to ensure lowest whole life cycle costs.
Mr Sinha said: “Currently, many of the maintenance regimes for wind farms are quite random, and we want to try and develop a system that will predict the failure of components and allow companies to carry out pre-planned action to lower the costs of maintenance.
“For this, we are developing a software tool that can assist in the timings of failures and the parts that would be needed.
“A downside for delayed or no maintenance is the financial loss that is linked with downtime of offshore wind turbines, which can be as high as £170/MWh – that is equal to £142,800 for a 5MW wind turbine which is down for one week.
“At present the cost of offshore wind turbine maintenance is as high as 35% of the total lifetime costs which equates to £14 billion a year for the 150 GW of offshore wind turbines which are predicted to be installed in Europe by 2030.
“So there is a need to control frequency of maintenance while ensuring that offshore wind turbines are available for the most time at a competitive price. The software tool being developed will assist companies to cut down on some of the costs and could save a lot of money which could then potentially be passed on to the consumer.”
Prof. Steel added: “Maintenance of wind turbines is costly and schemes designed to evaluate its failures will be an important step, not only towards improving reliability but also enabling companies to plan for a maintenance programme based on data from that particular wind farm.”
Mr Sinha said: “The potential impact that the software could have is very large. If there are ways of bringing down the costs of utilities, it could have a significant impact on the livelihood of many people.”