Abstract

Renewable energy sources such as wind energy
are available without any limitations. In order to extract
this energy efficiency, the reliability of such technologies is
critical if pay back periods and power generation requirements
are to be met. Due to recent developments in the
field of wind engineering and in particular the expansion of
installed capacity around the world, the need for reliable
and intelligent diagnostic tools is of greater importance.
The number of offshore wind turbines installed in the seas
around Britain’s coasts is likely to increase from just fewer
than 150–7,500 over the next 10 years with the potential
cost of £10 billion. Operation and Maintenance activities
are estimated to be 35 % against the cost of electricity.
However, the development of appropriate and efficient
maintenance strategies is currently lacking in the wind
industry. The current reliability and failure modes of offshore
wind turbines are known and have been used to
develop preventive and corrective maintenance strategies
which have done little to improve reliability. In addition,
the failure of one minor component can cause escalated
damage to a major component, which can increase repair
and or replacement costs. A reliability centered maintenance
(RCM) approach offers considerable benefit to the
management of wind turbine operations since it includes an
appreciation of the impact of faults on operations. Due to
the high costs involved in performing maintenance and the
even higher costs associated with failures and subsequent
downtime and repair, it is critical that the impacts are
considered when maintenance is planned. This paper provides
an overview of the application of RCM and on line
e-condition monitoring to wind turbine maintenance management.
Unplanned maintenance levels can be reduced by
increasing the reliability of the gear box and individual
gears through the analysis of lubricants. Finally the paper
will discuss the development of a complete sensor-based
processing unit that can continuously monitor the wind
turbines lubricated systems and provide, via wireless
technology, real time data enabling on shore staff with the
ability to predict degradation anticipate problems and take
remedial action before damage and failure occurs.