Scenario Analysis of Cost-Effectiveness of Maintenance Strategies for Fixed Tidal Stream Turbines in the Atlantic Ocean

• Published in: Journal of Marine Science and Engineering
• Main Authors: Mitra Kamidelivand, Peter Deeney, Fiona Devoy McAuliffe, Kevin Leyne, Michael Togneri, Jimmy Murphy
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2023
• Subjects: tidal stream turbine; stochastic O& M model; corrective and planned maintenance; annual failure rate; downtime; Naval architecture. Shipbuilding. Marine engineering; VM1-989; Oceanography; GC1-1581; Northeast Atlantic
• Online Access: https://doi.org/10.3390/jmse11051046; https://doaj.org/article/afaf60553b534a199b29cd4a22fb845b

This paper has developed an operation and maintenance (O&M) model for projected 20 MW tidal stream farm case studies at two sites in the northeast Atlantic in France and at EMEC’s Fall of Warness site in the UK. The annual energy production, number of incidents, and downtimes of the farms for corrective and planned (preventive) maintenance strategies are estimated using Monte Carlo simulations that vary weather windows, repair vessel availabilities, and mean annual failure rates modelled by Weibull distributions. The trade-offs between the mean annual failure rates, time availability, O&M costs, and energy income minus the variable O&M costs were analysed. For all scenarios, a 5-year planned maintenance strategy could considerably decrease the mean annual failure rates by 37% at both sites and increase the net energy income. Based on a detailed sensitivity analysis, the study has suggested a simple decision-making method that examines how the variation in the mean annual failure rate and changes in spare-part costs would reduce the effectiveness of a preventive maintenance strategy. This work provides insights into the most important parameters that affect the O&M cost of tidal stream turbines and their effect on tidal energy management. The output of the study will contribute to decision-making concerning maintenance strategies.