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Comparative analysis and improvement of grid-based wind farm layout optimization

机译:基于网格的风电场布局优化的比较分析与改进

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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.
机译:在文献中寻址的主要基于网格的风电场布局优化研究中,通过选择作为主要目标函数的调整能量成本来重新计算14项布局。依靠120个风力涡轮机组合,已经应用了以前显影的优化方法,然后应用了最佳涡轮机选择。所有文献布局都被优化,随着容量因素(略微)增加(略高于78.89-80.90至83.02-83.07%,而能源的调整成本(显着)减少(130.37-370.42至54.01-142.64 $ / mwh)。本研究得出结论,在所有场景中都可以建议离散和连续优化模型。通常,容量因数增加并不一定意味着降低了能量的稳定性成本。通过降低整体风力电力电力容量,涡轮机的数量或选择具有较低转子直径或额定功率的涡轮机来最小化后者。相反,可以通过安装具有更高集线器高度或更低额定速度的涡轮机来最大限度地最大限度地最大限度地。与各种调查结果相比,使用具有不同转子直径的涡轮机,不建议使用额定功率或轮毂高度来最小化能量的调整成本。虽然在几种优化研究中解决了,但最大化能量产量是误导性的目标,涉及能量最高的目标。

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