热电联产经济调度的改进遗传算法

IF 4.9 3区 计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY Journal of Bionic Engineering Pub Date : 2024-07-09 DOI:10.1007/s42235-024-00569-5
Deliang Li, Chunyu Yang
{"title":"热电联产经济调度的改进遗传算法","authors":"Deliang Li,&nbsp;Chunyu Yang","doi":"10.1007/s42235-024-00569-5","DOIUrl":null,"url":null,"abstract":"<div><p>Combined Heat and Power Economic Dispatch (CHPED) is an important problem in the energy field, and it is beneficial for improving the utilization efficiency of power and heat energies. This paper proposes a Modified Genetic Algorithm (MGA) to determine the power and heat outputs of three kinds of units for CHPED. First, MGA replaces the simulated binary crossover by a new one based on the uniform and guassian distributions, and its convergence can be enhanced. Second, MGA modifies the mutation operator by introducing a disturbance coefficient based on guassian distribution, which can decrease the risk of being trapped into local optima. Eight instances with or without prohibited operating zones are used to investigate the efficiencies of MGA and other four genetic algorithms for CHPED. In comparison with the other algorithms, MGA has reduced generation costs by at least 562.73$, 1068.7$, 522.68$ and 1016.24$, respectively, for instances 3, 4, 7 and 8, and it has reduced generation costs by at most 848.22$, 3642.85$, 897.63$ and 3812.65$, respectively, for instances 3, 4, 7 and 8. Therefore, MGA has desirable convergence and stability for CHPED in comparison with the other four genetic algorithms.</p></div>","PeriodicalId":614,"journal":{"name":"Journal of Bionic Engineering","volume":"21 5","pages":"2569 - 2586"},"PeriodicalIF":4.9000,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Modified Genetic Algorithm for Combined Heat and Power Economic Dispatch\",\"authors\":\"Deliang Li,&nbsp;Chunyu Yang\",\"doi\":\"10.1007/s42235-024-00569-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Combined Heat and Power Economic Dispatch (CHPED) is an important problem in the energy field, and it is beneficial for improving the utilization efficiency of power and heat energies. This paper proposes a Modified Genetic Algorithm (MGA) to determine the power and heat outputs of three kinds of units for CHPED. First, MGA replaces the simulated binary crossover by a new one based on the uniform and guassian distributions, and its convergence can be enhanced. Second, MGA modifies the mutation operator by introducing a disturbance coefficient based on guassian distribution, which can decrease the risk of being trapped into local optima. Eight instances with or without prohibited operating zones are used to investigate the efficiencies of MGA and other four genetic algorithms for CHPED. In comparison with the other algorithms, MGA has reduced generation costs by at least 562.73$, 1068.7$, 522.68$ and 1016.24$, respectively, for instances 3, 4, 7 and 8, and it has reduced generation costs by at most 848.22$, 3642.85$, 897.63$ and 3812.65$, respectively, for instances 3, 4, 7 and 8. Therefore, MGA has desirable convergence and stability for CHPED in comparison with the other four genetic algorithms.</p></div>\",\"PeriodicalId\":614,\"journal\":{\"name\":\"Journal of Bionic Engineering\",\"volume\":\"21 5\",\"pages\":\"2569 - 2586\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2024-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Bionic Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s42235-024-00569-5\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Bionic Engineering","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s42235-024-00569-5","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

热电联产经济调度(CHPED)是能源领域的一个重要问题,有利于提高电能和热能的利用效率。本文提出了一种修正遗传算法(MGA)来确定 CHPED 中三种机组的功率和热量输出。首先,MGA 以基于均匀分布和瓜斯分布的新遗传算法取代了模拟的二元交叉,从而提高了收敛性。其次,MGA 通过引入基于瓜西安分布的干扰系数来修改突变算子,从而降低了陷入局部最优的风险。我们使用了八个有或没有禁止操作区的实例来研究 MGA 和其他四种遗传算法在 CHPED 中的效率。与其他算法相比,MGA 在实例 3、4、7 和 8 中分别减少了至少 562.73 美元、1068.7 美元、522.68 美元和 1016.24 美元的发电成本,在实例 3、4、7 和 8 中分别减少了最多 848.22 美元、3642.85 美元、897.63 美元和 3812.65 美元的发电成本。因此,与其他四种遗传算法相比,MGA 在 CHPED 方面具有理想的收敛性和稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Modified Genetic Algorithm for Combined Heat and Power Economic Dispatch

Combined Heat and Power Economic Dispatch (CHPED) is an important problem in the energy field, and it is beneficial for improving the utilization efficiency of power and heat energies. This paper proposes a Modified Genetic Algorithm (MGA) to determine the power and heat outputs of three kinds of units for CHPED. First, MGA replaces the simulated binary crossover by a new one based on the uniform and guassian distributions, and its convergence can be enhanced. Second, MGA modifies the mutation operator by introducing a disturbance coefficient based on guassian distribution, which can decrease the risk of being trapped into local optima. Eight instances with or without prohibited operating zones are used to investigate the efficiencies of MGA and other four genetic algorithms for CHPED. In comparison with the other algorithms, MGA has reduced generation costs by at least 562.73$, 1068.7$, 522.68$ and 1016.24$, respectively, for instances 3, 4, 7 and 8, and it has reduced generation costs by at most 848.22$, 3642.85$, 897.63$ and 3812.65$, respectively, for instances 3, 4, 7 and 8. Therefore, MGA has desirable convergence and stability for CHPED in comparison with the other four genetic algorithms.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Bionic Engineering
Journal of Bionic Engineering 工程技术-材料科学:生物材料
CiteScore
7.10
自引率
10.00%
发文量
162
审稿时长
10.0 months
期刊介绍: The Journal of Bionic Engineering (JBE) is a peer-reviewed journal that publishes original research papers and reviews that apply the knowledge learned from nature and biological systems to solve concrete engineering problems. The topics that JBE covers include but are not limited to: Mechanisms, kinematical mechanics and control of animal locomotion, development of mobile robots with walking (running and crawling), swimming or flying abilities inspired by animal locomotion. Structures, morphologies, composition and physical properties of natural and biomaterials; fabrication of new materials mimicking the properties and functions of natural and biomaterials. Biomedical materials, artificial organs and tissue engineering for medical applications; rehabilitation equipment and devices. Development of bioinspired computation methods and artificial intelligence for engineering applications.
期刊最新文献
Sandwich-Structured Solar Cells with Accelerated Conversion Efficiency by Self-Cooling and Self-Cleaning Design From Perception to Action: Brain-to-Brain Information Transmission of Pigeons Design and Motion Characteristics of a Ray-Inspired Micro-Robot Made of Magnetic Film Bionic Jumping of Humanoid Robot via Online Centroid Trajectory Optimization and High Dynamic Motion Controller Multi-Sensor Fusion for State Estimation and Control of Cable-Driven Soft Robots
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1