论文标题
风电场布局的拓扑优化
Topology optimization of wind farm layouts
论文作者
论文摘要
提出了一种解决风电场布局优化问题解决方案的新方法。每年的能源产量受到最小和最大风力涡轮机数量以及风力涡轮机之间的最小间距的限制。所提出的方法依赖于基于密度的拓扑优化方法，其中连续密度变量在零和一个之间变化为每个潜在的风力涡轮机位置。如果风力涡轮机相关变量等于一个，则存在一个，否则如果关联变量为零，则不存在。密度变量的中间值通过传统上在多物质结构拓扑优化的背景下使用的插值方案进行惩罚。设计变量的惩罚中间值变得不经济，并且优化算法被隐式地推向了Crisp 0-1最终值的偏好。基于一阶信息的基于梯度的算法解决了优化问题。由于提出的问题制定，涉及的功能是根据设计变量明确提出的，可以直接计算其分析梯度。数值结果突出了所提出的方法在发现远离直觉风电场布局的能力，这些布局具有少量的计算资源和时间。
A novel approach for the solution of the wind farm layout optimization problem is presented. The annual energy production is maximized with constraints on the minimum and maximum number of wind turbines placed, and on the minimum spacing between the wind turbines. The proposed approach relies on a density-based topology optimization method, where continuous density variables varying between zero and one are assigned to each potential wind turbine location. A wind turbine exists if its associated variable equals one, otherwise it does not exist if the associated variable is zero. Intermediate values of the density variables are penalized with interpolation schemes traditionally used in the context of multi-material structural topology optimization. The penalized intermediate values of the design variables become uneconomical and the optimization algorithm is implicitly pushed towards a preference of crisp 0-1 final values. The optimization problem is solved with a gradient-based algorithm based on first-order information. Because of the proposed problem formulation, the functions involved are formulated explicitly in terms of the design variables and their analytical gradients can be calculated directly. The numerical results highlight the capability of the proposed approach in finding far from intuitive wind farm layouts with small computational resources and time.
