Modified Jaya Optimization Algorithm for Combined Economic Emission Dispatch Solution

Swaraj Banerjee, Dipu Sarkar
{"title":"Modified Jaya Optimization Algorithm for Combined Economic Emission Dispatch Solution","authors":"Swaraj Banerjee, Dipu Sarkar","doi":"10.18178/ijoee.6.1.13-19","DOIUrl":null,"url":null,"abstract":"The Combined Economic Emission Dispatch (CEED) problem focuses on the short-term determination of optimal generation from a number of power generating units in a way such that both generation costs and emission levels become minimum simultaneously, while satisfying all operational constraints and the load demand. The CEED problem considers the environmental impacts from the gaseous emission of pollutants at fossil-fueled power generating plants. This paper presents the formulation of the CEED problem as a multi-objective problem which in turn has been converted into a single objective function considering price penalty factor. This article proposes a new optimization algorithm, Modified Jaya Optimization Algorithm (MJOA), for CEED problem solution. The existing Jaya Optimization Algorithm (JOA) has been slightly modified to formulate the MJOA for faster convergence and robustness. Later the modified algorithm has been implemented in two test systems to investigate and ensure the effectiveness. The simulation results of the modified algorithm have been compared with other exiting algorithms, present in literature and MJOA has proved to be the best and most powerful amongst them.","PeriodicalId":13951,"journal":{"name":"International Journal of Electrical Energy","volume":"326 1","pages":"13-19"},"PeriodicalIF":0.0000,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Electrical Energy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18178/ijoee.6.1.13-19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The Combined Economic Emission Dispatch (CEED) problem focuses on the short-term determination of optimal generation from a number of power generating units in a way such that both generation costs and emission levels become minimum simultaneously, while satisfying all operational constraints and the load demand. The CEED problem considers the environmental impacts from the gaseous emission of pollutants at fossil-fueled power generating plants. This paper presents the formulation of the CEED problem as a multi-objective problem which in turn has been converted into a single objective function considering price penalty factor. This article proposes a new optimization algorithm, Modified Jaya Optimization Algorithm (MJOA), for CEED problem solution. The existing Jaya Optimization Algorithm (JOA) has been slightly modified to formulate the MJOA for faster convergence and robustness. Later the modified algorithm has been implemented in two test systems to investigate and ensure the effectiveness. The simulation results of the modified algorithm have been compared with other exiting algorithms, present in literature and MJOA has proved to be the best and most powerful amongst them.
联合经济排放调度方案的改进Jaya优化算法
联合经济排放调度(CEED)问题关注的是在满足所有运行约束和负荷需求的情况下,以发电成本和排放水平同时最小的方式,从多个发电机组中确定最优发电。CEED问题考虑了化石燃料发电厂气体排放污染物对环境的影响。本文提出了将CEED问题转化为考虑价格惩罚因素的单目标函数的多目标问题的形式。本文提出了一种新的求解CEED问题的优化算法——改进Jaya优化算法(MJOA)。对现有的Jaya优化算法(JOA)进行了一些修改,使其具有更快的收敛速度和鲁棒性。随后在两个测试系统中实施了改进算法,以检验和保证算法的有效性。将改进算法的仿真结果与文献中已有的算法进行了比较,结果表明MJOA算法是其中性能最好、功能最强大的算法。
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
来源期刊
自引率
0.00%
发文量
0
×
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