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Spatial Dependence in Wind and Optimal Wind Power Allocation: A Copula Based Analysis

机译:风和空间依赖风和最优风电分配:基于Copula的分析

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摘要

The investment decision on the placement of wind turbines is, neglecting legal formalities, mainly driven by the aim to maximize the expected annual energy production of single turbines. The result is a concentration of wind farms at locations with high average wind speed. While this strategy may be optimal for single investors maximizing their own return on investment, the resulting overall allocation of wind turbines may be unfavorable for energy suppliers and the economy because of large ufb02uctuations in the overall wind power output. This paper investigates to what extent optimal allocation of wind farms in Germany can reduce these ufb02uctuations. We analyze stochastic dependencies of wind speed for a large data set of German on- and oufb00shore weather stations and ufb01nd that these dependencies turn out to be highly nonlinear but constant over time. Using copula theory we determine the value at risk of energy production for given allocation sets of wind farms and derive optimal allocation plans. We ufb01nd that the optimized allocation of wind farms may substantially stabilize the overall wind energy supply on daily as well as hourly frequency.
机译:风力涡轮机的安置投资决策忽略了法律手续,这主要是由旨在使单个涡轮机的预期年发电量最大化的目标驱动的。结果是风电场集中在平均风速高的位置。尽管此策略可能对单个投资者而言是最大的最大化其自身投资回报的最佳选择,但由于整体风力发电量较大,因此风力涡轮机的总体配置可能对能源供应商和经济不利。本文研究了德国风电场的最佳配置可以在多大程度上减少这些影响。我们分析了德国陆上和oufb00海岸气象站的大量数据的风速随机相关性,并且 ufb01nd证明这些相关性是高度非线性的,但随时间变化是恒定的。使用copula理论,我们确定给定风电场分配集的能源生产风险价值,并得出最佳分配计划。我们认为,风电场的优化配置可以使每天以及每小时的风能供应总体稳定。

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