An optimization framework for daily route planning and scheduling of maintenance vessel activities in offshore wind farms. (1st April 2021)

• Record Type: Journal Article
• Authors: Lazakis, Iraklis; Khan, Shahroz
• Is Part Of: Ocean engineering. Volume 225(2021)
• Publication Date: 2021-04-01
• Subjects: Offshore wind farm -- Service operation vessel (SOV) -- Crew transfer vessel (CTV) -- Optimal route planning -- Reduction of fuel consumption -- Maintenance operation -- Maintenance cost reduction; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2021.108752
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: To increase energy production, offshore wind farms are currently installed far from shore, providing a challenge for vessels to undertake maintenance tasks from the designated hub port. Service Operation Vessels (SOVs) are utilized to carry out the offshore wind turbines maintenance tasks, which act as a servicing station having required technicians and daughter crafts (i.e. Crew Transfer Vessels (CTV)) onboard to facilitate on-time and on-demand servicing of wind turbines. This paper proposes an optimization framework, called OptiRoute, for daily or short-term maintenance operations based on route planning and scheduling while minimizing the cost under different operational constraints. Different heuristic and clustering techniques are developed and integrated to make the framework computationally effective. OptiRoute considers climate data, vessels specifications, failure information, wind farm attributes and cost-related specifics. The series of the overall operational tasks are divided into sequential sessions, including maintenance crew pick-up and drop-off tasks while the vessel routing optimization is performed for all sessions separately. OptiRoute reliability is tested by employing different Case studies while a user-friendly Graphical User Interface (GUI) is also developed to depict the various maintenance scheduling scenarios. Experimental results reveal that OptiRoute can efficiently increase the operational window especially when SOV and CTVs are used together. Highlights: A novel optimisation heuristic framework is proposed for optimal route planning of offshore wind maintenance vessels. A clustering technique is utilized to complete the offshore wind turbines maintenance with optimum number of vessels. Combination of climate data, vessels specifications, wind turbines failures/location, cost, technicians' drop-off/pick-up. A combination of case studies are presented optimally using Operation Service Vessel (SOV) and Crew Transfer Vessels (CTVs). Offshore wind vessels' operational modes integrated to increase their operating window and optimise fuel oil consumption.