Maintenance Activities Coordination for Offshore Wind Farms Integrating Multivariate Stochastic Models

ABSTRACT: The efficiency and reliability of offshore wind farms are significantly influenced by their maintenance strategies. Effective maintenance coordination is crucial to minimize downtime and consequently maximize reliability. This paper proposes a methodology for integrating multivariate stochastic models into the maintenance scheduling process of offshore wind farms, enabling a more data-driven approach. The proposed framework accounts for the temporal and spatial dependencies of wind variations to optimize maintenance activities, ensuring minimal disruptions to energy production using the Expected Energy Not Supplied (EENS) indicator. We validate our approach using case studies that demonstrate its effectiveness through a sensitivity analysis. The results highlight more than 6% deviations in the EENS estimate for scenarios with the same conditions, where the only difference is the wind speed simulation approach. The change in approach impacts the overall allocation of maintenance activities to offshore wind farms.

KEYWORDS: Environment Protection, Meteorological Conditions, Marine Engineering, Marine Environment, Offshore Industry, Renewable energy, Offshore Wind Energy, Maintenance of Offshore Structures

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Citation note:

Salgado Duarte Y., Szpytko J.: Maintenance Activities Coordination for Offshore Wind Farms Integrating Multivariate Stochastic Models. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 19, No. 2, doi:10.12716/1001.19.02.19, pp. 491-501, 2025

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