基于改进灰狼算法的定日镜场布局优化方法  

IMPROVED GREY WOLF OPTIMIZATION ALGORITHM FOR HELIOSTATS FIELD LAYOUT

作　　者：谢七月 刘广帅 刘瑶 申忠利 付强 周育才[1] Xie Qiyue;Liu Guangshuai;Liu Yao;Shen Zhongli;Fu Qiang;Zhou Yucai(School of Electrical and Information Engineering,Changsha University of Science and Technology,Changsha 410114,China)

机构地区：[1]长沙理工大学电气与信息工程学院,长沙410114

出　　处：《太阳能学报》2024年第11期394-400,共7页Acta Energiae Solaris Sinica

基　　金：国家自然科学基金(62373067);湖南省自然科学基金(2021JJ30740)。

摘　　要：提出一种基于改进灰狼算法的塔式太阳能热发电电站定日镜场优化布局方法,该改进算法将灰狼优化算法与记忆、局部搜索和进化算子相结合,增强了算法的全局性和搜索精度。以西班牙Gemasolar塔式太阳能热发电电站为例验证算法的有效性,使用改进灰狼算法对该电站定日镜场布局优化后,定日镜场光学效率提升5%,证明定日镜场布局经过改进灰狼算法优化后有更高的年平均光学效率。A method for optimizing the layout of the heliostat field in tower solar thermal power plants based on the improved gray wolf optimization algorithm is proposed.This improved algorithm combines the gray wolf optimization algorithm with memory,local search and evolutionary operators to enhance the global nature and search accuracy of the algorithm.Taking the Gemasolar solar thermal power plant in Spain as an example to verify the effectiveness of the algorithm,after using the improved gray wolf optimization algorithm to optimize the layout of the heliostat field in the power station,the optical efficiency of the heliostat field increased by 5%,which proves that the heliostat field layout has a higher average annual optical efficiency after being optimized by the improved gray wolf algorithm.

关 键 词：定日镜 聚光太阳能热发电 优化 改进灰狼算法 镜场布局 光学效率 

分 类 号：TK513.1[动力工程及工程热物理—热能工程]