期刊
ENERGY CONVERSION AND MANAGEMENT
卷 208, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2020.112593
关键词
Wind farm layout optimization; Gridded layout; Literature case study; Wind turbine database; Levelized cost of energy; Self-organizing map
Among the main grid-based wind farm layout optimization studies addressed in the literature, 14 layouts have been recomputed by selecting the levelized cost of energy as a primary objective function. Relying on 120 wind turbine combinations, a previously developed optimization method targeting best turbine selection has then been applied. All literature layouts were optimized, as capacity factors were (slightly) increased (78.89-80.90 to 83.02-83.07%), while levelized costs of energy were (significantly) reduced (130.37-370.42 to 54.01-142.64 $/MWh). This study concluded that neither the discrete nor the continuous optimization model can be recommended in all scenarios. In general, a capacity factor increase does not necessarily imply a decrease in levelized cost of energy. The latter may be minimized by decreasing the overall wind farm capacity, the number of turbines, or selecting turbines with lower rotor diameters or rated powers. By contrast, capacity factor may be maximized by installing turbines with higher hub heights or lower rated speeds. Contradicting various findings, using turbines with different rotor diameters, rated powers or hub heights is not recommended to minimize the levelized cost of energy. Although addressed within several optimization studies, maximization of energy production is a misleading target, as involving the highest costs of energy.
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