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基于网格-坐标化遗传算法的风电场布局优化
引用本文:蒋秋俊,郑海涛,杨庆山,周绪红,黄国庆,林毅峰. 基于网格-坐标化遗传算法的风电场布局优化[J]. 太阳能学报, 2022, 43(8): 266-272. DOI: 10.19912/j.0254-0096.tynxb.2020-1302
作者姓名:蒋秋俊  郑海涛  杨庆山  周绪红  黄国庆  林毅峰
作者单位:1.西南交通大学数学学院统计系,成都 611730; 2.重庆大学土木工程学院,重庆 400045; 3.上海勘测设计研究院有限公司,上海 200434
基金项目:国家自然科学基金(52178456); 111引智基地项目(B18062)
摘    要:采用Jensen尾流模型来描述风电机组间尾流的干扰效应。首先基于网格化的改进遗传算法获得风电机组的数量和布局初始位置,再通过坐标化遗传算法对风电机组位置进行进一步调整优化,从而提高单位成本的发电量。根据所提出的方法,在3种不同的风场(定风向定风速、定风速变风向和变风速变风向)下,针对2 km×2 km的标准风场区域进行风电机组布局优化,再将其应用到不规则的实际案例,对比分析表明所提出的方法能有效提高发电量。

关 键 词:优化  遗传算法  风电场  网格  坐标  不规则区域  
收稿时间:2020-12-03

WIND FARM LAYOUT OPTIMIZATION BASED ON GRID-COORDINATE GENETIC ALGORITHM
Jiang Qiujun,Zheng Haitao,Yang Qingshan,Zhou Xuhong,Huang Guoqing,Lin Yifeng. WIND FARM LAYOUT OPTIMIZATION BASED ON GRID-COORDINATE GENETIC ALGORITHM[J]. Acta Energiae Solaris Sinica, 2022, 43(8): 266-272. DOI: 10.19912/j.0254-0096.tynxb.2020-1302
Authors:Jiang Qiujun  Zheng Haitao  Yang Qingshan  Zhou Xuhong  Huang Guoqing  Lin Yifeng
Affiliation:1. Department of Statistics, School of Mathematics, Southwest Jiaotong University, Chengdu 611730, China; 2. School of Civil Engineering, Chongqing University, Chongqing 400045, China; 3. Shanghai Investigation, Design & Research Institute Co., Ltd., Shanghai 200434, China
Abstract:In this paper,Jensen's wake model is adopted to describe the interference effect of the wake among wind turbines. The number of wind turbines and the initial position of the layout are obtained based on the improved grid genetic algorithm,then the coordinated genetic algorithm is used to further optimize the position of the wind turbines,thereby increasing the power generation per unit cost. With the proposed method,three different wind scenarios (single wind direction,multiple wind directions with constant intensity and multiple wind directions with various intensities) are considered and the turbine layout optimization was carried out for the standard 2 km×2 km wind farm and the irregular wind farm. Comparative analysis shows that the proposed method can effectively increase power generation.
Keywords:optimization  genetic algorithm  wind farm  grid  coordinate  irregular area  
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