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Optimal placement of wind turbines: A Monte Carlo approach with large historical data set

机译:风力涡轮机的最佳布置:具有大量历史数据的蒙特卡洛方法

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Numerous technical issues arise with the close spacing of multiple wind turbines in a wind farm, particularly one with a severely limited spatial footprint. One of the most important factors under consideration is the wake effect. Since the energy losses due to wakes can significantly decrease the energy production and lead to fluctuations in the output power of a wind farm it is desired to determine optimal positions for installing multiple wind turbines. In the current study, an algorithm that determines an optimal positioning of multiple wind mills in a small footprint wind park under multiple wake effects is introduced. This approach is a mathematical method which explores the various possible positioning combinations via a Monte Carlo-like random search methodology and finds the best choice which maximizes the objective. Matlab (©Mathworks) is used to numerically generate the algorithm and obtain an optimal solution. The case study considered for implementing this algorithm is the Minnesota State University 2-year grant project for installation and testing of four small wind turbine systems on campus. Statistical data from the Weather Analysis Laboratory for Teaching and Educational Resources (WALTER) on campus, consisting of wind speed and direction data over a period of one year is considered to determine the annual power generated.
机译:在风电场中的多个风力涡轮机的近距离出现了许多技术问题,特别是具有严重限制的空间足迹。正在考虑的最重要因素之一是唤醒效果。由于由于唤醒引起的能量损失可以显着降低能量产生并导致风电场的输出功率波动,希望确定用于安装多个风力涡轮机的最佳位置。在目前的研究中,引入了一种在多个唤醒效果下确定多个挡风机中的多个风铣刀的最佳定位的算法。该方法是一种数学方法,其通过蒙特卡罗样随机搜索方法探讨各种可能的定位组合,并找到最佳选择,最大化目标。 MATLAB(©MATHWORKS)用于数值生成算法并获得最佳解决方案。考虑实施该算法的案例研究是明尼苏达州立大学的2年拨款项目,用于在校园内进行四个小型风力涡轮机系统的安装和测试。来自校园教学和教育资源(Walter)的天气分析实验室的统计数据,包括在一年内的风速和方向数据组成,以确定产生的年权力。

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