In order to increase the performance of horizontal tidal turbines, a multi-objective optimization model was proposed in this study. Firstly, the prediction model for horizontal tidal turbines was built, which coupled ...In order to increase the performance of horizontal tidal turbines, a multi-objective optimization model was proposed in this study. Firstly, the prediction model for horizontal tidal turbines was built, which coupled the blade element momentum (BEM) theory and the CFD calculation. Secondly, a multi-objective optimization method coupled the response surface method (RSM) with the multi-objective genetic algorithm NSGA-II was applied to obtain the optimal blade profiles. The pitch angle and the chord length distribution were chosen as the design variables, while the mean power coefficient and the variance of power coefficient were chosen as the objective functions. With the mean power coefficient improved by 4.1% and the variance of power coefficient decreased by 46.7%, results showed that both objective functions could be improved.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant Nos.51706198 and 51839010)the Zhejiang Provincial Natural Science Foundation of China(Grant No.LQ17E090004)
文摘In order to increase the performance of horizontal tidal turbines, a multi-objective optimization model was proposed in this study. Firstly, the prediction model for horizontal tidal turbines was built, which coupled the blade element momentum (BEM) theory and the CFD calculation. Secondly, a multi-objective optimization method coupled the response surface method (RSM) with the multi-objective genetic algorithm NSGA-II was applied to obtain the optimal blade profiles. The pitch angle and the chord length distribution were chosen as the design variables, while the mean power coefficient and the variance of power coefficient were chosen as the objective functions. With the mean power coefficient improved by 4.1% and the variance of power coefficient decreased by 46.7%, results showed that both objective functions could be improved.
