Cost Benefit of Implementing Advanced Monitoring and Predictive Maintenance Strategies for Offshore Wind Farms

Abstract

Advancements in wind turbine condition monitoring systems over the last decade have made it possible to optimise operational performance and reduce costs associated with component failure and other unplanned maintenance activities. While much research focuses on providing more automated and accurate fault diagnostics and prognostics in relation to predictive maintenance, efforts to quantify the impact of such strategies have to date been comparatively limited. Through time-based simulation of wind farm operation, this paper quantifies the cost benefits associated with predictive and condition-based maintenance strategies, taking into consideration both direct O&M costs and lost production. Predictive and condition-based strategies have been modelled by adjusting known component failure and repair rates associated with a more reactive approach to maintenance. Results indicate that up to 8% of direct O&M costs can be saved through early intervention along with up to 11% reduction in lost production, assuming 25% of major failures of the generator and gearbox can be diagnosed through advanced monitoring and repaired before major replacement is required. Condition-based approaches can offer further savings compared to predictive strategies by utilising more component life before replacement. However, if weighing up the risk between component failure and replacing a component too early, results suggest that it is more cost effective to intervene earlier if heavy lift vessels can be avoided, even if that means additional major repairs are required over the lifetime of the site.

Inspection of Floating Offshore Wind Turbines Using Multi-Rotor Unmanned Aerial Vehicles: Literature Review and Trends

“…Mechanical components always cause a higher amount of downtime when compared to electrical/control ones, reaching more than 75% of the total downtime [81]. Studies have found that approximately 19.4% of wind turbine failures are about blades [73].…”

Intelligent Electric Grid Maintenance via an Adaptive Predictive Maintenance Optimization Algorithm

“…Challenges are also prevalent in post-sale maintenance services, primarily due to the unpredictability of asset performance and the complexities involved in managing the maintenance workflow [30]. Despite these obstacles, there are effective strategies to overcome them and ensure the successful implementation of sophisticated maintenance methods [31]. These include delineating residents' patient panels, embracing a team-centric care model, and integrating maintenance strategies into educational curricula and clinical training.…”

Maritime logistics optimisation for predictive maintenance at offshore wind farms

“…The success of a model for the smart maintenance logistic problem for offshore wind farms is reliant on the implementation of advanced monitoring systems and good models for estimating remaining useful life of components and hence form the basis for the predictive maintenance strategy. [43] presents a cost benefit analysis of implementing advanced monitoring and predictive maintenance strategies for offshore wind farms and concludes that a potential cost reduction of up to 8% could be achieved in direct O&M costs and up to 11% reduction in lost production. Digital twins [44] combined with the offshore wind turbines control and monitoring systems can be used in combination with a smart maintenance logistics optimisation model to achieve a high potential O&M cost reduction, and increased power production from the wind turbines.…”