Influence of uncertainty on performance of opportunistic maintenance strategy for offshore wind farms

Conference Paper (2021)
Author(s)

M. Li (TU Delft - Transport Engineering and Logistics)

Xiaoli Jiang (TU Delft - Transport Engineering and Logistics)

James Carroll (University of Strathclyde)

R. R. Negenborn (TU Delft - Transport Engineering and Logistics)

Research Group
Transport Engineering and Logistics
Copyright
© 2021 M. Li, X. Jiang, James Carroll, R.R. Negenborn
DOI related publication
https://doi.org/10.23919/OCEANS44145.2021.9706074
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 M. Li, X. Jiang, James Carroll, R.R. Negenborn
Research Group
Transport Engineering and Logistics
ISBN (print)
978-1-6654-2788-3
ISBN (electronic)
978-0-692-93559-0
Reuse Rights

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Abstract

The increasing capacity of offshore wind energy around the world brings challenges in Operation and Maintenance (O&M) management. Over the past years, many studies have focused on developing sound maintenance strategies in order to minimize maintenance cost or maximize availability. One of the promising maintenance strategies is opportunistic maintenance due to its potential to combine maintenance activities and save maintenance efforts. In these models, a common assumption is made that input parameters are deterministic and maintenance decisions are made based on these assumed deterministic input parameters. However, offshore wind farm maintenance in the practical world is a complicated task where multiple types of uncertainty exist. These uncertainties may affect evaluation or output of the maintenance model, making maintenance decisions sub-optimal or even inappropriate. In this paper, a probabilistic simulation-based approach integrating an uncertainty module and a simulation module is proposed to study the influence of the uncertainties on maintenance performance. We identify the primary input parameters which should be considered as uncertainty but are simplified to be deterministic values in offshore wind energy maintenance models. These deterministic parameters are modelled as stochastic values in the uncertainty module to generate uncertainty scenarios. The simulation module for opportunistic maintenance is developed to quantity the expected maintenance cost and lost production. The most influential uncertainties are identified. Valuable information and suggestions are provided to offshore wind farm owners for future decision-making and project management.

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