A decision support system for strategic maintenance planning in offshore wind farms. (December 2016)

• Record Type: Journal Article
• Authors: Li, Xiaodong; Ouelhadj, Djamila; Song, Xiang; Jones, Dylan; Wall, Graham; Howell, Kerry E.; Igwe, Paul; Martin, Simon; Song, Dongping; Pertin, Emmanuel
• Is Part Of: Renewable energy. Volume 99(2016)
• Page Start: 784
• Page End: 799
• Publication Date: 2016-12
• Subjects: Offshore wind -- Renewable energy -- Operations and maintenance (O&M) -- Decision support -- Stochastic optimisation; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2016.07.037
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: 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. Highlights: A Decision Support System is designed for multiple offshore wind stakeholders. A deterministic model is intended for users with access to accurate failure rate. A stochastic model is intended for users who have less certainty about failure. Maintenance resources are identified to meet the requirement of workload.