Multi-objective optimization of the life-cycle costs and reliability of offshore wind turbines (WTs) is an area of immense interest due to the widespread increase in wind power generation across the world. Though there has been significant research done in this field for structures such as bridges and offshore oil and gas platforms, less research has been conducted for the costs and reliability optimization of offshore WTs. Most of the existing studies have addressed the conjunction of structural reliability and the Bayesian pre-posterior analysis for multi-objective optimization. This paper proposes and extension of the previous approaches as a novel framework for multi-objective probabilistic optimization of the total life-cycle costs and reliability of WTs by combining the elements of structural reliability analysis, Bayesian pre-posterior analysis with neuro-fuzzy and evolutionary algorithms. The output of this framework would determine the optimal inspection, monitoring and maintenance schedules to be conducted during the life span of the offshore WTs while maintaining a trade-off between the life-cycle costs and reliability of the structure.
|Title of host publication||Proceedings of 2nd International Conference on Offshore Renewable Energy|
|Place of Publication||Glasgow|
|Number of pages||10|
|Publication status||Published - 2016|