On the importance of assessing the operational context impact on maintenance management for life cycle cost of wind energy projects.

The increasing demand for energy from renewable sources is entailing the development of technologies oriented to increase the profitability of such projects and thus the attractiveness for potential investors. Wind power constitutes one of the most relevant renewable energy sources; however, the costs of the wind farms associated with Operations & Maintenance are prominent along the life-cycle. This paper proposes an approach intended to reduce these costs and lower the Levelized Cost of Energy. In this context, it is presented an opportunistic maintenance policy based on more accurate reliability estimates of the wind turbines components. The reliability of the components is estimated through a model based on Artificial Neural Networks that dynamically calculates the impact of operational conditions on the failures of the wind turbines. The approach has been validated through a case study based on real field data which proposes a multi-objective optimization of the maintenance strategy for the life-cycle of a wind farm. The obtained results provide interesting findings from the perspective of wind farms investors, operators, and owners. • Life-cycle approach for the maintenance management of wind farms considering operational environment. • Dynamic reliability model based on Artificial Neural Networks. • Comparison of several scenarios entailing different maintenance strategies and reliability models. • Case study based on real field data to see the benefits of the proposed approach. • Extensive experimentation and optimizations to validate results. [ABSTRACT FROM AUTHOR]