Quantifying the Potential Logistic Benefits of a Predictive Maintenance Strategy in Offshore Wind Farms

December 10, 2021

The present work aims to quantify the potential benefits of a predictive maintenance strategy in offshore wind farms, benchmarking these benefits against corrective maintenance. The predictive maintenance is also tested for five different predictive periods, here referring to how many days ahead a failure can be predicted. To quantify these benefits, two analyses are performed based on a computational model developed in Python for this purpose, built with a module-based structure. Firstly, a wind farm analysis assesses the potential benefits that predictive maintenance can bring to a wind farm. Then, a component-level analysis aims to statistically quantify total failure costs variability throughout the year, for each maintenance strategy and subassembly. Statistical logistic benefits in the total failure costs are also found. In general, major cost decreases are found in a 5-day predictive period. Wind farm results show that the lowest total wind farm costs, and highest energetic availability, were found for a 20-day predictive period. However, these total cost results are close to the results from the 10-day predictive period. The component level results show that different subassemblies have different logistic benefits, but similar benefits are found for the same maintenance type. The total failure cost benefits of the subassemblies’ replacements vary from 1.4% to 3.2%, major repairs from 13.3% to 19.6%, and minor repairs from 56.4% to 60.5%.

Authors in the community:

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  M

  Márcio António Rodrigues Pedroso

  ist197047

Supervisors of this institution:

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  R

  Ricardo Balbino Santos Pereira

  ist151719

mechanical-engineering - Mechanical engineering

por - Portuguese

Instituto Superior Técnico