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Automatic Contour-Based Road Network Design for Optimized Wind Farm Micrositing

机译:基于轮廓的自动路网设计,优化风电场选址

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Constructing the access roads between wind turbines requires a significant cost when a wind farm is built in hills or mountains. An optimized design of road network can substantially reduce construction costs and increase investment returns. In this paper, we consider a challenging problem of the road network design for a wind farm with complex topography. An automatic contour-based model is developed for road network design, and is incorporated into the optimization of wind farm micrositing to maximize investment returns of the wind farm. The directions of access roads are first deduced from a contour tree, the route projections are then designed by a gradient-bounded algorithm, and the most cost-effective road network is finally obtained by the minimum spanning tree algorithm. The topographic speedup, wind resource grid and Park wake model are incorporated to accurately evaluate the power production of the wind farm. Both the profit of wind energy sales and the cost of access roads are combined into a cost function called net present value, which is optimized using genetic algorithms. Simulation results illustrate that the length of access roads is decreased significantly while the locations of wind turbines are optimized. The proposed method simultaneously optimizes the turbine layout and road network of the wind farm, therefore achieving a more practical and profitable wind farm micrositing.
机译:当在丘陵或山区建造风电场时,在风力涡轮机之间建造出入口道路需要大量成本。道路网络的优化设计可以大大降低建设成本并增加投资回报。在本文中,我们考虑了具有复杂地形的风电场道路网络设计的挑战性问题。为道路网络设计开发了基于轮廓的自动模型,并将其纳入风电场微观选址的优化中,以最大化风电场的投资回报。首先从等高线树中得出出入道路的方向,然后通过梯度有界算法设计路线投影,最后通过最小生成树算法获得最具成本效益的路网。结合了地形加速,风资源网格和Park唤醒模型,可以准确评估风电场的发电量。风能销售的利润和通行道路的成本都被合并到一个称为净现值的成本函数中,该函数使用遗传算法进行了优化。仿真结果表明,在优化风轮机位置的同时,可大大缩短通道的长度。所提出的方法同时优化了风电场的涡轮机布局和道路网络,因此实现了更实用和更有利的风电场微选址。

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