Algorithms for Offshore Wind Farm Layout Optimization

被引:84
作者
Elkinton, Christopher [1 ]
Manwell, James [1 ]
McGowan, Jon [1 ]
机构
[1] Univ Massachusetts, Dept Mech & Ind Engn, Renewable Energy Res Lab, 160 Governors Dr, Amherst, MA 01003 USA
关键词
Simulated annealing;
D O I
10.1260/030952408784305877
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Offshore wind energy is positioned to facilitate substantial growth in wind energy production, but further reductions in the cost of energy will strengthen its ability to compete directly with other energy generating technologies. One simple solution is the optimal use of current technologies. To this end, this study investigates the use of optimization algorithms for offshore wind farm micrositing. First, a discussion is given of five different types of optimization algorithms: gradient search, heuristic, pattern search, simulated annealing, and evolutionary algorithms. The relevance of each algorithm to wind turbine micrositing is then evaluated by considering two separate objectives: minimization of the levelized production cost and maximization of the energy production. The genetic and greedy heuristic algorithms are further evaluated through the use of design simulations. Finally, these algorithms are employed to optimize the layout of a potential, real-world offshore wind farm near Hull, Massachusetts.
引用
收藏
页码:67 / 84
页数:18
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