With lower turbulence and less rigorous restrictions on noise levels,offshore wind farms provide favourable conditions for the development of high-tip-speed wind turbines.In this study,the multi-objective optimization...With lower turbulence and less rigorous restrictions on noise levels,offshore wind farms provide favourable conditions for the development of high-tip-speed wind turbines.In this study,the multi-objective optimization is presented for a 5MW wind turbine design and the effects of high tip speed on power output,cost and noise are analysed.In order to improve the convergence and efficiency of optimization,a novel type of gradient-based multi-objective evolutionary algorithm is proposed based on uniform decomposition and differential evolution.Optimization examples of the wind turbines indicate that the new algorithm can obtain uniformly distributed optimal solutions and this algorithm outperforms the conventional evolutionary algorithms in convergence and optimization efficiency.For the 5MW wind turbines designed,increasing the tip speed can greatly reduce the cost of energy(COE).When the tip speed increases from 80m/s to 100m/s,under the same annual energy production,the COE decreases by 3.2%in a class I wind farm and by 5.1%in a class III one,respectively,while the sound pressure level increases by a maximum of 4.4dB with the class III wind farm case.展开更多
基金This work was funded by the National Basic Research Program of China(973 Program)(No.2014CB046200)the National Nature science Foundation(No.51506089)+1 种基金the Jiangsu Provincial Natural Science Foundation(No.BK20140059)the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘With lower turbulence and less rigorous restrictions on noise levels,offshore wind farms provide favourable conditions for the development of high-tip-speed wind turbines.In this study,the multi-objective optimization is presented for a 5MW wind turbine design and the effects of high tip speed on power output,cost and noise are analysed.In order to improve the convergence and efficiency of optimization,a novel type of gradient-based multi-objective evolutionary algorithm is proposed based on uniform decomposition and differential evolution.Optimization examples of the wind turbines indicate that the new algorithm can obtain uniformly distributed optimal solutions and this algorithm outperforms the conventional evolutionary algorithms in convergence and optimization efficiency.For the 5MW wind turbines designed,increasing the tip speed can greatly reduce the cost of energy(COE).When the tip speed increases from 80m/s to 100m/s,under the same annual energy production,the COE decreases by 3.2%in a class I wind farm and by 5.1%in a class III one,respectively,while the sound pressure level increases by a maximum of 4.4dB with the class III wind farm case.
