A Cost Optimisation Model for Maintenance Planning in Offshore Wind Farms with Wind Speed Dependent Failure Rates

Xiaodong Li (), Xiang Song and Djamila Ouelhadj
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Xiaodong Li: School of Computing and Creative Technologies, University of the West of England, Bristol BS16 1QY, UK
Xiang Song: School of Mathematics and Physics, University of Portsmouth, Portsmouth PO1 2UP, UK
Djamila Ouelhadj: School of Mathematics and Physics, University of Portsmouth, Portsmouth PO1 2UP, UK

Mathematics, 2023, vol. 11, issue 13, 1-21

Abstract: This paper presents an optimisation model for cost optimisation of maintenance at an offshore wind farm (OWF). The model is created for OWF project developers to optimise strategic resources to meet their maintenance demand. The model takes into account various maintenance categories on a full range of wind turbine components; the failure rate associated with each component is dependent on wind speed in order to consider weather uncertainty. Weibull distribution is used to predict the probability of wind speed occurring during a given period based on available historical data. The performance of the proposed optimisation model has been validated using reference cases and a UK OWF in operation. Various optimal solutions are investigated for the problems with increased and decreased mean turbine failure rates as a sensitivity test of the model.

Keywords: offshore wind; renewable energy; operations and maintenance (O&M); decision making; cost optimisation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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