Predictive Modelling of Dynamic Positioning Vessel Capacity on Offshore Wind Industry - Kim, JeongMin; Park, Hyeri (Sustainable Marine Structures, 2025)
As global efforts to combat climate change intensify, offshore wind farms have emerged as scalable and sustainable solutions. However, their deployment depends heavily on the availability of specialized vessels with Dynamic Positioning (DP) systems such as Wind Turbine Installation Vessels (WTIVs) and Service Operation Vessels (SOVs). Despite their importance, long-term demand forecasting for such vessels remains underexplored, especially in South Korea. This study presents the dDP-W model, a System Dynamics (SD)-based framework that simulates the evolving demand for DP vessels under varying technological, policy, and environmental conditions. Unlike conventional methods based on historical extrapolation, the model uses feedback-driven causality and scenario-based simulations aligned with South Korea’s offshore wind roadmap (2026–2036). Three WTIV demand scenarios—baseline, optimistic, and pessimistic—were constructed based on vessel productivity and weather-related downtime. SOV demand was estimated using cumulative turbine counts and fixed vessel coverage ratios. The simulations indicate that WTIV demand peaks in the early 2030s, requiring 6 to 7 vessels depending on conditions, while SOV demand increases steadily, reaching nearly 70 vessels by 2036. These findings highlight the need for early vessel procurement, infrastructure investment, and workforce preparation. By integrating technical, logistical, and policy factors into a dynamic model, this study provides a practical decision-support tool for stakeholders in shipbuilding and offshore energy. The results offer strategic insights to address potential vessel shortages and ensure alignment with national renewable energy goals. ER