• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.131-139
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• 2024

Crew Transfer Vessels (CTVs) are primarily used for the maintenance of offshore wind farms. Despite being manually operated by professional captains and crew, collisions with other ships and marine structures still occur. To prevent this, the introduction of autonomous navigation systems to CTVs is necessary. In this study, research on the obstacle avoidance system of the autonomous navigation system for CTVs was conducted. In particular, research on obstacle avoidance simulation for CTVs using deep reinforcement learning was carried out, taking into account the currents and wind loads in offshore wind farms. For this purpose, 3 degrees of freedom ship maneuvering modeling for CTVs considering the currents and wind loads in offshore wind farms was performed, and a simulation environment for offshore wind farms was implemented to train and test the deep reinforcement learning agent. Specifically, this study conducted research on obstacle avoidance maneuvers using MATD3 within deep reinforcement learning, and as a result, it was confirmed that the model, which underwent training over 10,000 episodes, could successfully avoid both static and moving obstacles. This confirms the conclusion that the application of the methods proposed in this study can successfully facilitate obstacle avoidance for autonomous navigation CTVs within offshore wind farms.

• Journal of Wind Energy
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• v.14 no.3
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• pp.61-68
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• 2023

This paper aims to perform optimal operation and maintenance with an integrated monitoring system for offshore wind platforms. Based on the wind direction and wind speed data of existing wind farms, a monitoring system was established along with weather and weather data to maximize the operational efficiency of wind farms. Compared to wind power on land, offshore wind power is difficult to maintain due to weather, logistics and geographical limitations. Therefore, economic analysis of actual operation and maintenance is essential for large-scale offshore wind farms. In this paper, the availability of offshore wind farms was analyzed by using personnel resources, parts inventory, Crew Transfer Vessel (CTV) and Specialized service Operation Vessel (SOV) etc. before the actual operation and maintenance of wind farms. A comparative analysis was conducted to determine the optimum operating efficiency and economical maintenance costs.