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Solving Wind Farm Layout Optimization with Mixed Integer Programming and Constraint Programming

机译:用混合整数规划和约束规划求解风电场布局优化

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The wind farm layout optimization problem is concerned with the optimal location of turbines within a fixed geographical area to maximize energy capture under stochastic wind conditions. Previously it has been modelled as a maximum diversity (or p-dispersion-sum) problem, but such a formulation cannot capture the nonlinearity of aerodynamic interactions among multiple wind turbines. We present the first constraint programming (CP) and mixed integer linear programming (MIP) models that incorporate such nonlinearity. Our empirical results indicate that the relative performance between these two models reverses when the wind scenario changes from a simple to a more complex one. We also propose an improvement to the previous maximum diversity model and demonstrate that the improved model solves more problem instances.
机译:风电场布局优化问题与固定地理区域内的涡轮机的最佳位置有关,以在随机风况下最大程度地捕获能量。以前,它已被建模为最大分集(或p-色散和)问题,但是这种表述无法捕获多个风力涡轮机之间空气动力学相互作用的非线性。我们提出了结合了这种非线性的第一个约束规划(CP)和混合整数线性规划(MIP)模型。我们的经验结果表明,当风况从简单模式更改为更复杂模式时,这两个模型之间的相对性能会反转。我们还建议对先前的最大分集模型进行改进,并证明改进的模型可以解决更多问题实例。

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