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Conference programme 

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Poster session

Lead Session Chair:
Stephan Barth, Managing Director, ForWind - Center for Wind Energy Research, Germany
Guy Blonce (1) F P José Miguel Garate (2)
(1) ALSTOM RENEWABLES, Barcelona, Spain

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Presenter's biography

Biographies are supplied directly by presenters at OFFSHORE 2015 and are published here unedited

Mr. Blonce has been working in the wind industry for almost 4 years. He is currently RAMS engineer at Alstom Renewables in Barcelona. He studied computer science and telecommunications high technical cycle at C.E.S.F. in Barcelona. After his studies he spent 18 years at different companies and various roles of RAMS, Quality and SW responsible. He has been involved in different projects ATV, Ariane and VEGA lauchers for Space sector, L9 of metro in Barcelona for Railway sector and finally in Eolic sector for Offshore and Onshore wind turbines. His work is focused on RAMS process.


Haliade 150 6mw rams process for reliability improvement and validation.


Reliability Availability Maintainability and Safety (RAMS) analysis and modelling for design improvement, is a methodology wide used in other industries as railway, avionic-aerospace and in military environment. For those industries RAMS is standard for the development of new products and benefits of years of feedback of experience from the field data.
However wind industry and particularly offshore, is in the early stages of adapting RAMS as a design and validation methodology of the developed technologies and miss the necessary feedback of experience for proper studies comparing theoretical models versus field data.


This paper presents the approach followed during the new Haliade 150 wind turbine design, by means of a theoretical RAMS model to evaluate and validate the requirements defined at wind turbine, system and subsystem level. Furthermore a data reporting analysis and corrective action system (DRACAS) is defined to close de feedback of experience of the developed RAMS model with field data and results showed for such comparison of the ECO122 wind turbine model.

Main body of abstract

The Haliade 150 wind turbine has been developed according to specific reliability and availability targets. Those targets have been breakdown to the main systems and subsystems and have been used by the engineers as a driver for the development of the systems. As part of the RAMS model definition, in a first step, a system functional diagram (SFD) is generated with the list of all the components and their interrelation. In a second step a failure mode effects analysis (FMEA) is conducted and finally a reliability block diagram is model in a commercial software introducing the reliability data (MTBF, MTTR) of each component. As a conclusion for this loop a comparison with the requirements was performed and in case of deviation the necessary design loops were executed to meet them. In the second phase of the project a DRACAS system was defined where the main information of field operational data is stored: identifications (Wind farm, wind turbine), time of stoppage, cause of the incident (by system / subsystem), visit required to the wind turbine, spare part required for repair. In the third phase of the project as a validation of the methodology the full process is applied for a ECO122 wind turbine obtaining a comparison between the theoretical RAMS model and the field data.


The presented process of theoretical RAMS model development for new designs and later comparison of the model to the field data through the developed DRACAS systems shows to be accurate to perform a qualitative comparison that pointed the more critical system and advance future design strategies to achieve the global objective of improving wind technology reliability.
More effort and future work are required to analyse the quantitative differences between theoretical and field models and to extend the validation of the process to the offshore environment.

Learning objectives
The integration of a RAMS process in the wind turbine product development life cycle and the validation of the model through field feedback of experience to add value on the current and future product designs.