基于定点选择和遗传算法的风电场布局优化

Rabia Shakoor, M. Y. Hassan, Abdur Raheem, Nadia Rasheed, M. N. Mohd Nasir
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引用次数: 22

摘要

目前,风能产业在提高发电量方面面临着重大的设计制约。这些都可以通过在合适的地方安装合适的涡轮机来克服。本文提出了一种采用定点选择(DPS)和遗传算法的风电场优化布局设计,使单位功率成本最小,尾迹效应最小,同时保持相邻风机之间的必要间距,保证运行安全。通过改变风电场的面积,可以降低现有的单位功率成本。本研究采用jensen尾迹模型计算了各涡轮尾迹引起的速度亏损。将风电场总面积2 Km × 2 Km划分为10×10单元,每个单元尺寸为200 m × 200 m。结果表明,在风力机总数相同的情况下,使用相同面积的风电场在不同维度上的输出功率都有所增加。结果表明,在2 Km × 2 Km区域内,32台风力发电机组可产生16251.56 kW的总功率,适应度值为0.001537。本文的研究结果在前人研究结果的基础上得到了验证。
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Wind farm layout optimization by using Definite Point selection and genetic algorithm
At present, wind energy industry is facing major design constraints in boosting the power output. These can be overcome by setting up the right turbine at the right place. This paper proposes an optimized layout design of a wind farm by using Definite Point selection(DPS) and genetic algorithm, which can minimize the cost per unit power and minimum wake effects, while sustaining the obligatory space between adjacent turbines for operation safety. The existing cost per unit power can be reduced by changing the dimensions of wind farm with constant area. In this study, the velocity deficits caused by the wakes of each turbine were calculated by using Jensens wake model. The total area of wind farm 2 Km × 2 Km was divided into 10×10 cells with each cell having dimensions 200 m × 200 m. The results showed that power output of the wind farm by using the same area in different dimension was increased even when the total numbers of wind turbines were the same. It was observed that 32 wind turbines in 2 Km × 2 Km area could produce a total power of 16,251.56 kW with fitness value of 0.001537. The present research results had been validated using the results from previous studies.
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