|Appears in Collections:||Computing Science and Mathematics Journal Articles|
|Peer Review Status:||Refereed|
|Title:||A decision support system for strategic maintenance planning in offshore wind farms|
Howell, Kerry E
Operations and maintenance (O&M)
|Citation:||Li X, Ouelhadj D, Song X, Jones D, Wall G, Howell KE, Igwe P, Martin S, Song D & Pertin E (2016) A decision support system for strategic maintenance planning in offshore wind farms, Renewable Energy, 99, pp. 784-799.|
|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.|
|Rights:||Accepted refereed manuscript of: Li X, Ouelhadj D, Song X, Jones D, Wall G, Howell KE, Igwe P, Martin S, Song D & Pertin E (2016) A decision support system for strategic maintenance planning in offshore wind farms, Renewable Energy, 99, pp. 784-799. DOI: 10.1016/j.renene.2016.07.037 © 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/|
|Renewable Energy Final paper-12-7-16.pdf||1.22 MB||Adobe PDF||View/Open|
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