Numerical data for wind turbine micrositing inspired by human dynasties by use of the Dynastic Optimization Algorithm (DOA)

Shafiq-ur-Rehman Massan, Asim Imdad Wagan, Muhammad Mujtaba Shaikh
{"title":"Numerical data for wind turbine micrositing inspired by human dynasties by use of the Dynastic Optimization Algorithm (DOA)","authors":"Shafiq-ur-Rehman Massan, Asim Imdad Wagan, Muhammad Mujtaba Shaikh","doi":"10.17993/3ctecno/2020.v9n2e34.71-85","DOIUrl":null,"url":null,"abstract":"This work presents the newly formulated Dynastic Optimization Algorithm, DOA as applied to the wind \nturbine micrositing problem. The data is acquired by the use of the standard MATLAB software at a \nwind speed of 12 m/s. The values of the efficiency of the algorithm, cost per installation of per unit \nturbine, and total dissipated power at each number of turbines installed are discussed. \nThis algorithm is applied to two test functions and the results are described therein. It has been welldemonstrated \nthat the proposed DOA exhibits superior performance over GA and DEA for test functions \nby hitting the minima very often and with higher precision. On the other hand DOA performance on \nWTM problem is also encouraging.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17993/3ctecno/2020.v9n2e34.71-85","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This work presents the newly formulated Dynastic Optimization Algorithm, DOA as applied to the wind turbine micrositing problem. The data is acquired by the use of the standard MATLAB software at a wind speed of 12 m/s. The values of the efficiency of the algorithm, cost per installation of per unit turbine, and total dissipated power at each number of turbines installed are discussed. This algorithm is applied to two test functions and the results are described therein. It has been welldemonstrated that the proposed DOA exhibits superior performance over GA and DEA for test functions by hitting the minima very often and with higher precision. On the other hand DOA performance on WTM problem is also encouraging.
分享
查看原文
基于动态优化算法(DOA)的受人类王朝启发的风力机微定位数值数据
本文提出了一种新的动态优化算法DOA,并将其应用于风力涡轮机的微定位问题。通过使用标准MATLAB软件在12 m/s的风速下获取数据。讨论了算法的效率值、每台机组涡轮机的每次安装成本以及每台安装的涡轮机的总耗散功率。该算法被应用于两个测试函数,并在其中描述了结果。已经很好地证明,对于测试函数,所提出的DOA表现出优于GA和DEA的性能,因为它经常达到最小值,并且具有更高的精度。另一方面,在WTM问题上的DOA性能也令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信