Application of GA, PSO and ABC in optimal design of a stand-alone hybrid system for north-west of Iran

Application of GA, PSO and ABC in optimal design of a stand-alone hybrid system for north-west of Iran

In this paper, a novel intelligent method is applied to the problem of optimal design hybrid power system for supplying the isolated load demand. The purpose of this design is to optimize the costs during the 20-year operation system. This system includes photovoltaic, wind and a lead-acid battery b...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Javadi, M. R., Mazlumi, K., Jalilvand, A.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Batteries
Genetic algorithms
Hybrid power systems
Reliability
Wind speed
Wind turbines
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page I-210
container_issue
container_start_page I-203
container_title
container_volume
creator Javadi, M. R.
Mazlumi, K.
Jalilvand, A.
description In this paper, a novel intelligent method is applied to the problem of optimal design hybrid power system for supplying the isolated load demand. The purpose of this design is to optimize the costs during the 20-year operation system. This system includes photovoltaic, wind and a lead-acid battery bank. Using optimization methods of Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) the optimal capacity of these sources is determined. The objective function is minimized and the efficiency of this system in different operation situations. The input data of this paper is real and north western remote areas of Iran is studied. Covering the load demand under various weather conditions is the main constraint in this study.
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6140254</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6140254</ieee_id><sourcerecordid>6140254</sourcerecordid><originalsourceid>FETCH-ieee_primary_61402543</originalsourceid><addsrcrecordid>eNp9jcsKwjAURCMi-OoXuLkfYOFG02iXtfhaKejCnUSb2kiblCQg_XuruHY2A3MOTIcMOUZIEWO8dMmQMr6YI-XI-iRw7oltOI_pkg1IntR1qe7CK6PB5LBNpnA8HUDoDJJVCqpda68qUUImnXp8JQHOt0IoSqMlFM3Nqgxc47ysIDcWtLG-CF_S-Y-9t0KPSS8XpZPBr0dkslmf012opJTX2rYHtrlyynAWsfl_-gYKaEFo</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Application of GA, PSO and ABC in optimal design of a stand-alone hybrid system for north-west of Iran</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Javadi, M. R. ; Mazlumi, K. ; Jalilvand, A.</creator><creatorcontrib>Javadi, M. R. ; Mazlumi, K. ; Jalilvand, A.</creatorcontrib><description>In this paper, a novel intelligent method is applied to the problem of optimal design hybrid power system for supplying the isolated load demand. The purpose of this design is to optimize the costs during the 20-year operation system. This system includes photovoltaic, wind and a lead-acid battery bank. Using optimization methods of Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) the optimal capacity of these sources is determined. The objective function is minimized and the efficiency of this system in different operation situations. The input data of this paper is real and north western remote areas of Iran is studied. Covering the load demand under various weather conditions is the main constraint in this study.</description><identifier>ISBN: 1467301604</identifier><identifier>ISBN: 9781467301602</identifier><identifier>EISBN: 605010090X</identifier><identifier>EISBN: 9786050102048</identifier><identifier>EISBN: 605010204X</identifier><identifier>EISBN: 9786050100907</identifier><language>eng</language><publisher>IEEE</publisher><subject>Batteries ; Genetic algorithms ; Hybrid power systems ; Reliability ; Wind speed ; Wind turbines</subject><ispartof>2011 7th International Conference on Electrical and Electronics Engineering (ELECO), 2011, p.I-203-I-210</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6140254$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6140254$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Javadi, M. R.</creatorcontrib><creatorcontrib>Mazlumi, K.</creatorcontrib><creatorcontrib>Jalilvand, A.</creatorcontrib><title>Application of GA, PSO and ABC in optimal design of a stand-alone hybrid system for north-west of Iran</title><title>2011 7th International Conference on Electrical and Electronics Engineering (ELECO)</title><addtitle>ELECO</addtitle><description>In this paper, a novel intelligent method is applied to the problem of optimal design hybrid power system for supplying the isolated load demand. The purpose of this design is to optimize the costs during the 20-year operation system. This system includes photovoltaic, wind and a lead-acid battery bank. Using optimization methods of Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) the optimal capacity of these sources is determined. The objective function is minimized and the efficiency of this system in different operation situations. The input data of this paper is real and north western remote areas of Iran is studied. Covering the load demand under various weather conditions is the main constraint in this study.</description><subject>Batteries</subject><subject>Genetic algorithms</subject><subject>Hybrid power systems</subject><subject>Reliability</subject><subject>Wind speed</subject><subject>Wind turbines</subject><isbn>1467301604</isbn><isbn>9781467301602</isbn><isbn>605010090X</isbn><isbn>9786050102048</isbn><isbn>605010204X</isbn><isbn>9786050100907</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNp9jcsKwjAURCMi-OoXuLkfYOFG02iXtfhaKejCnUSb2kiblCQg_XuruHY2A3MOTIcMOUZIEWO8dMmQMr6YI-XI-iRw7oltOI_pkg1IntR1qe7CK6PB5LBNpnA8HUDoDJJVCqpda68qUUImnXp8JQHOt0IoSqMlFM3Nqgxc47ysIDcWtLG-CF_S-Y-9t0KPSS8XpZPBr0dkslmf012opJTX2rYHtrlyynAWsfl_-gYKaEFo</recordid><startdate>201112</startdate><enddate>201112</enddate><creator>Javadi, M. R.</creator><creator>Mazlumi, K.</creator><creator>Jalilvand, A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201112</creationdate><title>Application of GA, PSO and ABC in optimal design of a stand-alone hybrid system for north-west of Iran</title><author>Javadi, M. R. ; Mazlumi, K. ; Jalilvand, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_61402543</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Batteries</topic><topic>Genetic algorithms</topic><topic>Hybrid power systems</topic><topic>Reliability</topic><topic>Wind speed</topic><topic>Wind turbines</topic><toplevel>online_resources</toplevel><creatorcontrib>Javadi, M. R.</creatorcontrib><creatorcontrib>Mazlumi, K.</creatorcontrib><creatorcontrib>Jalilvand, A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Javadi, M. R.</au><au>Mazlumi, K.</au><au>Jalilvand, A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Application of GA, PSO and ABC in optimal design of a stand-alone hybrid system for north-west of Iran</atitle><btitle>2011 7th International Conference on Electrical and Electronics Engineering (ELECO)</btitle><stitle>ELECO</stitle><date>2011-12</date><risdate>2011</risdate><spage>I-203</spage><epage>I-210</epage><pages>I-203-I-210</pages><isbn>1467301604</isbn><isbn>9781467301602</isbn><eisbn>605010090X</eisbn><eisbn>9786050102048</eisbn><eisbn>605010204X</eisbn><eisbn>9786050100907</eisbn><abstract>In this paper, a novel intelligent method is applied to the problem of optimal design hybrid power system for supplying the isolated load demand. The purpose of this design is to optimize the costs during the 20-year operation system. This system includes photovoltaic, wind and a lead-acid battery bank. Using optimization methods of Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) the optimal capacity of these sources is determined. The objective function is minimized and the efficiency of this system in different operation situations. The input data of this paper is real and north western remote areas of Iran is studied. Covering the load demand under various weather conditions is the main constraint in this study.</abstract><pub>IEEE</pub></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 1467301604
ispartof 2011 7th International Conference on Electrical and Electronics Engineering (ELECO), 2011, p.I-203-I-210
issn
language eng
recordid cdi_ieee_primary_6140254
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Batteries
Genetic algorithms
Hybrid power systems
Reliability
Wind speed
Wind turbines
title Application of GA, PSO and ABC in optimal design of a stand-alone hybrid system for north-west of Iran
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T22%3A52%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Application%20of%20GA,%20PSO%20and%20ABC%20in%20optimal%20design%20of%20a%20stand-alone%20hybrid%20system%20for%20north-west%20of%20Iran&rft.btitle=2011%207th%20International%20Conference%20on%20Electrical%20and%20Electronics%20Engineering%20(ELECO)&rft.au=Javadi,%20M.%20R.&rft.date=2011-12&rft.spage=I-203&rft.epage=I-210&rft.pages=I-203-I-210&rft.isbn=1467301604&rft.isbn_list=9781467301602&rft_id=info:doi/&rft_dat=%3Cieee_6IE%3E6140254%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=605010090X&rft.eisbn_list=9786050102048&rft.eisbn_list=605010204X&rft.eisbn_list=9786050100907&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6140254&rfr_iscdi=true