求解动态经济排放调度问题的混合PSOGSA技术

IF 0.7 Q3 ENGINEERING, MULTIDISCIPLINARY

Engineering Review Pub Date : 2020-05-21 DOI:10.30765/er.40.3.10

H. Hardiansyah

{"title":"求解动态经济排放调度问题的混合PSOGSA技术","authors":"H. Hardiansyah","doi":"10.30765/er.40.3.10","DOIUrl":null,"url":null,"abstract":"In this paper, a new hybrid population-based algorithm is proposed with the combining of particle swarm optimization (PSO) and gravitational search algorithm (GSA) techniques. The main idea is to integrate the ability of exploration in PSO with the ability of exploration in the GSA to synthesize both algorithms’ strength. The new algorithm is implemented to the dynamic economic emission dispatch (DEED) problem to minimize both fuel cost and emission simultaneously under a set of constraints. To demonstrate the efficiency of the proposed algorithm, a 5-unit test system is used. The results show the effectiveness and superiority of the proposed method when compared to the results of other optimization algorithms reported in the literature.","PeriodicalId":44022,"journal":{"name":"Engineering Review","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2020-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.30765/er.40.3.10","citationCount":"1","resultStr":"{\"title\":\"Hybrid PSOGSA technique for solving dynamic economic emission dispatch problem\",\"authors\":\"H. Hardiansyah\",\"doi\":\"10.30765/er.40.3.10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new hybrid population-based algorithm is proposed with the combining of particle swarm optimization (PSO) and gravitational search algorithm (GSA) techniques. The main idea is to integrate the ability of exploration in PSO with the ability of exploration in the GSA to synthesize both algorithms’ strength. The new algorithm is implemented to the dynamic economic emission dispatch (DEED) problem to minimize both fuel cost and emission simultaneously under a set of constraints. To demonstrate the efficiency of the proposed algorithm, a 5-unit test system is used. The results show the effectiveness and superiority of the proposed method when compared to the results of other optimization algorithms reported in the literature.\",\"PeriodicalId\":44022,\"journal\":{\"name\":\"Engineering Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2020-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.30765/er.40.3.10\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30765/er.40.3.10\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30765/er.40.3.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 1

摘要

本文将粒子群优化(PSO)和引力搜索算法(GSA)相结合，提出了一种新的混合种群算法。其主要思想是将粒子群算法的探索能力与粒子群算法的探索能力相结合，综合两种算法的优势。将该算法应用于一组约束条件下的动态经济排放调度问题，使燃油成本和排放同时最小化。为了验证该算法的有效性，采用了一个5单元测试系统。与文献中报道的其他优化算法的结果相比，结果表明了所提方法的有效性和优越性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Hybrid PSOGSA technique for solving dynamic economic emission dispatch problem

In this paper, a new hybrid population-based algorithm is proposed with the combining of particle swarm optimization (PSO) and gravitational search algorithm (GSA) techniques. The main idea is to integrate the ability of exploration in PSO with the ability of exploration in the GSA to synthesize both algorithms’ strength. The new algorithm is implemented to the dynamic economic emission dispatch (DEED) problem to minimize both fuel cost and emission simultaneously under a set of constraints. To demonstrate the efficiency of the proposed algorithm, a 5-unit test system is used. The results show the effectiveness and superiority of the proposed method when compared to the results of other optimization algorithms reported in the literature.

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

Engineering Review ENGINEERING, MULTIDISCIPLINARY-

CiteScore

1.00

自引率

0.00%

发文量

期刊介绍： Engineering Review is an international journal designed to foster the exchange of ideas and transfer of knowledge between scientists and engineers involved in various engineering sciences that deal with investigations related to design, materials, technology, maintenance and manufacturing processes. It is not limited to the specific details of science and engineering but is instead devoted to a very wide range of subfields in the engineering sciences. It provides an appropriate resort for publishing the papers covering prior applications – based on the research topics comprising the entire engineering spectrum. Topics of particular interest thus include: mechanical engineering, naval architecture and marine engineering, fundamental engineering sciences, electrical engineering, computer sciences and civil engineering. Manuscripts addressing other issues may also be considered if they relate to engineering oriented subjects. The contributions, which may be analytical, numerical or experimental, should be of significance to the progress of mentioned topics. Papers that are merely illustrations of established principles or procedures generally will not be accepted. Occasionally, the magazine is ready to publish high-quality-selected papers from the conference after being renovated, expanded and written in accordance with the rules of the magazine. The high standard of excellence for any of published papers will be ensured by peer-review procedure. The journal takes into consideration only original scientific papers.