15 MW半潛式浮式風機系統新竹外海場址性能預測

Abstract

本研究探討在新竹外海地區使用半潛式臺大浮台、IEA 15-MW離岸風機以及3×3型式繫纜佈置之浮式風機系統的運轉性能及年平均發電功率。先以Ansys Aqwa和STAR-CCM+預測了水動力特性，再使用OrcaFlex預測繫纜受力及風機的空氣動力，最後通過運動方程式求解浮式風機系統的運動響應及發電功率。本研究假設波向與風向相同，使用了勢流方法及兩種黏性流方法預測水動力，計算在一般海況及極端條件下條件下的風機系統性能；對統計新竹外海長期的波況機率分佈，比較勢流與黏性流方法預測的下的水動力特性以及使用固定風速和API風譜的風機系統性能。模擬結果顯示，浮台的運動在使用單點黏性流方法下皆有低估的結果，並發現運動的大小與該海況的波能量尖峰處的阻尼大小相關。在極端海況下，使用全域黏性流方法的最大位移為8.293 m；最大纜繩張力為6.519 MN。在長期的情況下，使用API風譜的運動響應及繫纜張力最大值一般高於使用固定風速。在使用API風譜與全域黏性流方法的情況下，年平均容量因子可達0.512，與理論值相差1.8%。

This study explores the operational performance and capacity factor of a semi-submersible TaidaFloat platform featuring an IEA 15-MW offshore wind turbine and a 3×3 mooring configuration in the Hsinchu offshore area. Hydrodynamic properties are predicted using Ansys Aqwa and STAR-CCM+, while OrcaFlex is employed to estimate mooring loads, predict wind turbine aerodynamics, and solve motion equations for evaluating motion response, power output, and dynamic responses of the mooring system and wind turbine. Assuming alignment between wave and wind directions, the potential flow method (P) and two viscous methods are utilized to calculate the hydrodynamic properties of the studied FOWT system for predicting its operational performance under common and extreme wave conditions. Statistical analysis is used to bluid the scatter diagram of long-term conditions off Hsinchu for comparing hydrodynamic properties using both potential and viscous methods under a constant wind speed and API spectrum. The simulations reveal that the motion response of the platform is underestimated with the sigle-point method, where the motion magnitude is related to damping at the wave spectral density peak under specific metocean conditions. Under the extreme condition, the maximum offset using the fully viscous method is 8.293 m, with the highest mooring line tension at 6.519 MN. For long-term conditions, maximum values of motion response and mooring line tension were generally higher with the API wind spectrum compared to a constant wind speed. Employing the API wind spectrum and the fully viscous method, the annual average capacity factor was found to be 0.512, differing by 1.8% from the theoretical value.