Nonperiodic Inspection and Maintenance Optimization for Floating Wind Turbine Electric Control Systems Based on an Improved Salp Swarm Algorithm

Abstract Floating offshore wind turbines (FOWTs) are prone to failure due to harsh marine environments, and preventive maintenance (PM) is necessary to ensure that the system operates efficiently. This study aims to establish a PM strategy for the electric control system in the FOWT. The system degradation is modeled as a stochastic process following the Gamma distribution. The costs for implementing PM or corrective maintenance (CM) within the lifetime of the FOWT represent the economic performance of the maintenance strategy. In addition to the maintenance threshold, another key factor, the inspection time interval, is considered in the model to further improve the scheduling of maintenance actions. An improved salp swarm algorithm (ISSA) is adopted to determine the optimal maintenance strategy. The maintenance cost under nonperiodic inspection and maintenance is minimized to enhance the economic performance of the maintenance strategy. A case study is performed to demonstrate the superiority of the developed maintenance strategy. The results show that the optimal maintenance strategy results in an average daily saving of 60.1€ in the FOWT generator over a 25-year lifetime. Through numerical analysis of maintenance optimization, this study provides insights into enhancing the cost-effectiveness of the maintenance for FOWTs.