Job Scheduling of Corrective Maintenance as Offshore Wind Farm Resilience Factor

Abstract

The article presents a Job Scheduling Problem (JSP) in the context of Offshore Wind Farm (OWF) maintenance. The recent advancements in the offshore energy sector are inspired by EU ambitions to achieve 111 GW of offshore renewables by 2030. Consequently, the identifiable issue of performing even more efficient maintenance campaigns and troubleshooting operations emerges as a significant challenge. To address the problem, the concept of operational windows identification and utilization is introduced in the study. The obtained compositions of operational windows are transferred then to the scheduling procedure. Additional input is created with the time dependent list of offshore wind turbine failures based on empirical data. In the next step, selected methods of sorting the awaiting jobs are examined. The conducted study results in a number of schedules developed with various job prioritization methods. The quality of each schedule is estimated with the use of selected Key Performance Indicators (KPIs). In the context of system recovery as a resilience factor, performed analysis focuses on influence of scheduling algorithms on selected KPIs rather than on resources and their redundancy, which is the most common but expensive approach. The study supports the thesis that specific scheduling algorithms reduce the number of required vessels and personnel while improving selected KPIs. In the conclusion, the article highlights the need for holistic optimization approach and distinguish selected performance KPIs from system recovery indicators.