Optimal joint maintenance and orienteering strategy for complex mission-oriented systems: A case study in offshore wind energy

This paper introduces and solves the joint maintenance and orienteering problem with an application to offshore wind farms. The quest for sustainable energy production is fueling the growth of offshore wind electricity generation. Energy producing offshore wind turbines are typically dispersed across several remote wind farms and must be maintained and operated with high reliability levels for long time-periods separated by scheduled maintenance rotations. Due to resource constraints such as travel time, cost, and availability of repair crews, only a subset of turbines and their components can be selected for maintenance operations during maintenance trips. This paper proposes a novel joint maintenance and orienteering framework to address the selection of turbines to visit, the components to maintain, the maintenance levels to be performed, the assignment of repair crews, and their routing with the goal of minimizing total cost while satisfying a minimum required reliability threshold during the next operating mission until the next maintenance rotation. A mixed-integer linear programming optimization model is developed and fully discussed. To solve the problem for large-scale instances, a column generation method based on Dantzig-Wolfe decomposition and labeling algorithm is proposed. Several numerical experiments demonstrate the validity of the proposed model and the benefit of jointly optimizing maintenance and orienteering decisions. The results show that inclusion of detailed reliability and multiple maintenance levels allows better maintenance and routing decisions. Numerical results also show trade-offs between reliability requirement, shift duration and total cost.