Papers presented at ESREL
DNV GL Software 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 wind farms 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 wind farms. Maros and Taro have all the necessary features to perform an extensive study for wind farms.
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 away – with some additional challenges!
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. Maros and Taro features have been designed to the oil and gas industry but are flexible enough to be easily extended to wind farms.
RAM analysis for wind turbines involves a number of extra variables that must be taken into account such as:
- Power curve and wind speed profiles
- Statistical definition for wind speed
- Shutdown when the wind is too strong
The software products can easily account for these parameters. Features in the software such as flow-based events and probabilistic distributions to define the “feed” (i.e. Wind) are of fundamental importance to take into account the correct operations of a wind farm.
Maintenance strategy is one of many topics that can be explored in detail. For instance, when empowered with a RAM model, the analyst can explore a number of variables that will impact directly, not only the uptime of the system but also operational expenditure. Maros and Taro enable different strategies to be evaluated including planned inspections, condition based maintenance, spares management (offshore and onshore resources), crew management and supporting vessels. The software will then report the utilization of the resources as well as a repair delay factor which is a function of all constraints defined in the model.
DNV GL incorporates a vast expertise in this area from legacy DNV, Kema, Garrad Hassan and GL Renewables certification. RAM analysis for wind turbines is one of the supported analyses.