PREDICTIVE MAINTENANCE
FEATURE SPONSOR
WHOOSHING OPPORTUNITIES RAM ANALYSIS FOR WINDFARMS
DNV GL have recently published a whitepaper (link/s at the end of this editorial) to discuss the challenges in the Wind Turbine market in regards to maintenance and operations.
WINDFARMS
To give us some context, in March 2007, EU leaders set the 2020 targets, committing to address the (always) increasing energy production from hydrocarbon sources. The main goal is to become a highly energy-efficient and low carbon economy.
In this programme, they mention the 2020, 20-20-20 targets. The programme describes an integrated approach to climate and energy policy that aims to combat climate change. One of the “20” refers to increasing the share of EU energy consumption produced from renewable resources to 20%.
To achieve this target, wind turbines must play an essential role. Good news, one might say – a solution to the global issue. The bad news however, is how do we support a big “fan” sitting afar? In the same way we support a big metal structure far way – with some additional challenges!
24/7 OPERATION
Akin to an oil and gas production platform, the operation is 24/7. The wind turbines are unmanned, imposing challenges to maintenance campaigns. Space is also limited and only small spare parts can be stored in the turbine.
VICTOR BORGES EXPLAINS…
Recently, I attended ESREL (European Safety and Reliability Conference) where we presented a paper on balancing safety and performance through QRA and RAM. The conference was very informative – one of the discussion topics was energy production and distribution – with windfarms being a popular theme. A number of papers discussed operations and maintenance challenges using the Monte Carlo method to predict the performance of wind turbines, i.e. RAM analysis for windfarms.
RAM analysis for wind turbines involve a number of extra variables that must be taken into account such as…
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