London, UK [RenewableEnergyWorld.com] A project to develop and demonstrate a condition monitoring system, which could reduce the cost of generating electricity from offshore wind farms, has been launched by the Energy Technologies Institute (ETI).
The £5 million [US $7.5 million] condition monitoring project is being led by UK-based wind turbine blade monitoring specialists Insensys in partnership with EDF Energy, E.ON, Romax Technology, SeeByte and Strathclyde University.
The consortium will develop and demonstrate systems to monitor the condition and performance of turbines and predict future maintenance requirements for key components so they can be corrected before expensive damage occurs. The turbine conditioning monitoring system will cover all aspects of a turbine including the blades, bearings, gearbox, generator, power electronics and support structures.
Systems will be installed on onshore wind turbines and tested for 18 months, with a further year of tests planned for offshore wind turbines, to demonstrate the benefits and savings.
It is estimated that increased output, through reduced downtime, and reduced maintenance costs, could result in a benefit of up to £50,000 [US $75,000] per turbine, per year.
ETI Chief Executive Dr. David Clarke said: “Offshore Wind has huge potential to reduce UK carbon emissions and increase security of energy supply. However, barriers still exist before it can make a significant contribution to the UK’s energy demands. One of the main barriers is the higher operation and maintenance costs due to the challenges associated with operating offshore. If turbines fail they can be difficult and costly to repair which is why it is important to spot potential damage or performance deterioration as early as possible.” Clarke added: “The project will develop accurate models for predicting potential damage and fatigue to turbines providing early warnings and identifying the causes of possible component failures before expensive repairs are needed or the turbine fails. It will also aim to identify the causes of fatigue, which should allow early action to be taken to increase reliability.”