A Redundancy Optimization Model Applied to Offshore Wind Turbine Power Converters
Paper i proceeding, 2013

Unexpected failures, high operation and maintenance (O&M) cost, and low accessibility are critical issues for offshore wind farms. According to existing statistics, power converters are among the most critical components in offshore wind turbines, and suffer from a high failure rate. One efficient way to improve the reliability and availability of the converter system is by adding at least one independent redundant converter, which ensures that the system would still operate in case of a converter failure. However, the redundant converters will increase the system’s cost, volume, and weight. In this paper, we propose a cost-rate minimization model aiming to simultaneously determine the optimal allocation of redundant converters and the optimal number of the converters that are allowed to fail before sending a maintenance crew to the offshore platform. The optimal solution under system-level constraints is derived, and the conditions required to make using redundant converter system beneficial are discussed. Finally, the proposed model has been tested on data collected from an offshore wind farm database and the results are compared with a conventional wind turbine converter system.

Maintenance

Offshore wind turbine

Reliability

Redundancy optimization

Power converter

Författare

Mahmood Shafiee

Chalmers, Matematiska vetenskaper, Matematik

Göteborgs universitet

Michael Patriksson

Chalmers, Matematiska vetenskaper, Matematik

Göteborgs universitet

Ann-Brith Strömberg

Chalmers, Matematiska vetenskaper, Matematik

Göteborgs universitet

Lina Bertling

Chalmers, Energi och miljö, Elkraftteknik

PowerTech (POWERTECH), 2013 IEEE Grenoble

8article no 6652427)-
978-1-4673-5669-5 (ISBN)

Drivkrafter

Hållbar utveckling

Ämneskategorier

Beräkningsmatematik

Tillförlitlighets- och kvalitetsteknik

Elektroteknik och elektronik

Styrkeområden

Energi

DOI

10.1109/PTC.2013.6652427

ISBN

978-1-4673-5669-5

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Senast uppdaterat

2018-11-05