A decision support system for strategic maintenance planning in offshore wind farms

Li, Xiaodong; Ouelhadj, Djamila; Song, Xiang; Jones, Dylan; Wall, Graham; Howell, Kerry E.; Igwe, Paul; Martin, Simon; Song, Dongping; Pertin, Emmanuel

Abstract

© 2016 Elsevier Ltd This paper presents a Decision Support System (DSS) for maintenance cost optimisation at an Offshore Wind Farm (OWF). The DSS is designed for use by multiple stakeholders in the OWF sector with the overall goal of informing maintenance strategy and hence reducing overall lifecycle maintenance costs at the OWF. Two optimisation models underpin the DSS. The first is a deterministic model that is intended for use by stakeholders with access to accurate failure rate data. The second is a stochastic model that is intended for use by stakeholders who have less certainty about failure rates. Solutions of both models are presented using a UK OWF that is in construction as an example. Conclusions as to the value of failure rate data are drawn by comparing the results of the two models. Sensitivity analysis is undertaken with respect to the turbine failure rate frequency and number of turbines at the site, with near linear trends observed for both factors. Finally, overall conclusions are drawn in the context of maintenance planning in the OWF sector.

• Journal Article Type: Article
• Acceptance Date: Jul 16, 2016
• Online Publication Date: Jul 31, 2016
• Publication Date: Dec 1, 2016
• Deposit Date: Sep 5, 2016
• Publicly Available Date: Jul 31, 2017
• Journal: Renewable Energy
• Print ISSN: 0960-1481
• Electronic ISSN: 1879-0682
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 99
• Pages: 784-799
• DOI: https://doi.org/10.1016/j.renene.2016.07.037
• Keywords: offshore wind, renewable energy, operations and maintenance (O&M), decision support, stochastic optimisation
• Public URL: https://uwe-repository.worktribe.com/output/905514
• Publisher URL: http://dx.doi.org/10.1016/j.renene.2016.07.037
• Contract Date: Sep 6, 2016