Framework for the Optimization of Maintenance Planning for Offshore Wind Farms
Offshore Wind Farms, Offshore Wind Energy, O&M, Optimization, Artificial Intelligence, Operations Research.
The maintenance of offshore wind turbines represents a significant challenge for the expansion of wind energy production. Given their proximity to the coast, these turbines face rigorous operational conditions, which can complicate their economic viability. This challenge is a constant issue in specialized publications on Operations and Maintenance (O&M). European and emerging markets are planning the large-scale production of this form of energy, demanding the optimization of resources used in the installation and maintenance of these parks.Current research is focused on discussing numerical techniques commonly addressed in this context, aiming to guide more suitable strategies, schedules, and diagnostics for decisions regarding preventive, predictive, and corrective maintenance. While quantitative techniques are studied separately in problems from different theoretical fields, their integration into the understanding of technical aspects associated with maintenance decisions can have a positive impact, provided their advantages and disadvantages are known and adequately overcome.The various factors and dimensions observed in each analyzed work emphasize the importance of directing current research toward understanding what should be considered in the planning and control of maintenance for offshore wind park assets. In this regard, this research aims to identify elements aligned with the planner's purposes and seeks to develop a comprehensive framework, comprising approaches, techniques, and critical factors.Expected results include the formulation of proposals for new strategies and quantitative methods for optimizing operations and maintenance of offshore wind turbines. These approaches aim to prevent failures, reduce costs, and enhance operational efficiency, contributing to risk mitigation and uncertainty management in maintenance planning.