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A decision support system for strategic maintenance planning in offshore wind farms
Affiliation:1. Centre for Operational Research and Logistics (CORL), Department of Mathematics, University of Portsmouth, UK;2. Plymouth Business School, University of Plymouth, UK;3. Computational Heuristics Operational Research Decision Support Group, University of Stirling, UK;4. Management School, University of Liverpool, UK;5. Institut Superieur D''etudes Logistiques (ISEL), Le Havre University, France;1. School of Engineering, University of Portsmouth, UK;2. Fluid Structure Interaction Research Group, Faculty of Engineering and the Environment, University of Southampton, UK;1. Universidad Nacional Autónoma de México, Centro de Nanociencias y Nanotecnología, Ensenada, Baja California, C.P. 22860, Mexico;2. Centro de Investigación y Desarrollo Tecnológico en Electroquímica, Tijuana, Baja California, C.P. 22444, Mexico;3. Facultad de Ingeniería Química, Universidad Michoacana de San Nicolás de Hidalgo, Ciudad Universitaria, Morelia, Michoacán, 58060, Mexico;4. Institut de Recherches sur la Catalyse et l’Environnement de Lyon (IRCELYON), CNRS – Université Lyon I, Villeurbanne, France;1. Departamet d’Enginyeria Mecanica, Universitat Rovira i Virgili, Tarragona, Spain;2. Center of Computational Engineering and Integrated Design (CEID), Department of Mathematics and Physics, Lappeenranta University of Technology, Lappeenranta, Finland;1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, PR China;2. Industrial and Systems Engineering, The University of Tennessee, Knoxville, TN, USA;3. Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, PR China
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.
Keywords:Offshore wind  Renewable energy  Operations and maintenance (O&M)  Decision support  Stochastic optimisation
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