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Optimal Redundancy and Maintenance Strategy Decisions for Offshore Wind Power Converters
Cranfield University, UK.
Chalmers.
Chalmers.
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.ORCID iD: 0000-0003-4763-9429
2015 (English)In: International Journal of Reliability, Quality and Safety Engineering (IJRQSE), ISSN 0218-5393, Vol. 22, no 3, 1550015-1-1550015-24 p., 1550015Article in journal (Refereed) Published
Abstract [en]

Analysis of field failure data collected from various wind farm databases indicates that the power converters are among the most critical components in offshore wind turbines, since they suffer from a high failure rate. One efficient approach to enhance the reliability and availability of the wind power systems is through using a redundant converter design, in which a set of power converters is placed together in parallel. The main advantage of a multiple parallel converter system is that the failure of one converter will not necessarily lead to the failure of the entire system. It may however increase the wind turbine’s acquisition cost, volume, and weight. In this paper, we propose an approach of joint redundancy and maintenance strategy optimization for offshore wind power converters, aiming to simultaneously determine the “optimal allocation of redundant converters” and the “optimal threshold number of converters that are allowed to fail before sending a maintenance crew to the offshore platform”. The optimal solution under various system- level constraints (such as reliability, weight, and the available space in nacelle) is derived and the conditions required to make using a redundant system beneficial are discussed. The proposed design is applied to an offshore wind turbine system and its performance is evaluated using a Monte-Carlo simulation technique. Finally, the results are compared with the conventional power converter system and a sensitivity analysis is conducted in order to make the proposed approach applicable for the next generation of wind turbines. 

Place, publisher, year, edition, pages
World Scientific Publishing Company , 2015. Vol. 22, no 3, 1550015-1-1550015-24 p., 1550015
Keyword [en]
wind power, asset management, optimisation, electric power generation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering; Energy Technology
Identifiers
URN: urn:nbn:se:kth:diva-173887DOI: 10.1142/S0218539315500151Scopus ID: 2-s2.0-84932196851OAI: oai:DiVA.org:kth-173887DiVA: diva2:855740
Note

QC 20150922

Available from: 2015-06-15 Created: 2015-09-22 Last updated: 2017-12-04Bibliographically approved

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Bertling Tjernberg, Lina

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