Optimal maintenance management of offshore wind turbines by minimizing the costs

Renewable and sustainable energy production systems offer promising perspectives for the future, as their maintenance prices decrease, efficiency reliability increase, favouring competitiveness of this industry. Thereby, wind is one most used developed renewable energy, since it a cost-effective way to generate clean energy. Wind divided into onshore offshore depending on farm location. Offshore increasing its use. However, industry requires more maintenance, which also complicated do because environmental conditions. Setting best strategy becomes optimization problem with several objectives constraint functions. In paper, novel multi-objective defined solved real case studies by using Genetic Algorithms Particle Swarm Optimization minimize operational costs maximize performance turbines. The results both algorithms are compared considering scenarios in study. These show better optimal cost achieved, less computational solve it. Finally, influence model parameters studied performing sensitivity study, that shows importance preventive reduction corrective tasks.