A key hurdle to meet the ambitious renewable energy targets is the high levelized cost of offshore wind energy. With Operations and Maintenance (O&M) actions making up more than a quarter of the total costs, substantial research efforts have been undertaken to optimize these actions. In line with this overarching goal, this project focuses on O&M actions, specifically optimizing time-based maintenance strategies to minimize costs. Literature reveals a variety of methods developed, such as Remaining Useful Life (RUL) models, degradation models, reliability models and maintenance models to simulate Wind Turbine (WT) lifetimes, O&M actions and calculate costs. A majority of these studies only look at
single failure modes (FM) or multiple independent FMs. In the field of wind energy, there is a significant lack of research on failure interactions and degradation dependence between different components or FMs. This project aims to build a model that accounts for dependencies in degradation between different FMs. This model is further combined with a maintenance model to simulate maintenance actions and estimate corresponding O&M costs.

The proposed degradation-based maintenance model builds on a simplified in-house model developed by the Wind Energy group at TNO. A Markov model, built in Python, is used to represent the degradation process. This is further combined with copula functions to represent degradation dependencies, using available copula packages in Python. Inspection and maintenance functions are then integrated into the degradation model to simulate O&M actions within the WT lifetime. Each action incurs either one or a combination of costs due to inspection, maintenance or operation, from WT downtime. An extensive number of time-based strategies are modelled, with varying inspection intervals for each. Finally, the accumulated lifetime costs are calculated and compared for the various maintenance strategies. The inspection interval with the minimum lifetime costs is selected as the optimum maintenance
strategy. In order to verify the validity of the proposed model, the results of an existing research paper on degradation modelling for WT blades are first replicated.

After successful verification, case studies are carried out to apply the model to the degradation processes of offshore wind turbine (OWT) hydraulic pitch systems. This is an extremely critical system, crucial for both WT operation and safety with the highest failure rates among all WT systems. The case studies selected in this work cover two pitch FMs: hydraulic fluid leakage and hydraulic valve wear. The model is applied to the case of single FMs and the case of multiple FMs, both independent and dependent. For both the single FM models, different optimum inspection intervals and lifetime costs are obtained. A higher failure rate for one of the FMs is the basis for the increased optimum lifetime cost and the decreased optimum inspection interval. Comparing the direct summation of the results of two single FM models with the multiple FM independent model outputs dissimilar results. The independent model leads to a reduced inspection interval and slightly higher lifetime costs. For the dependent
case, a 39% reduction in the lifetime costs and an increase in the optimal inspection interval is
observed compared to the independent case. This results in cheaper and less frequent O&M actions for the dependent case.

This work shows that, compared to the other case studies, modelling dependency between FMs allows for improved O&M actions, resulting in lower costs. This methodology has the potential to be used in future multi-component or multi-FM studies. The inclusion of degradation dependencies between components would better model the inter-dependencies between FMs and hence allow for improved optimization of O&M strategies.