Marine predators algorithm for solving single-objective optimal power flow

This study presents a nature-inspired, and metaheuristic-based Marine predator algorithm (MPA) for solving the optimal power flow (OPF) problem. The significant insight of MPA is the widespread foraging strategy called the Levy walk and Brownian movements in ocean predators, including the optimal en...

Full description

Saved in:
Bibliographic Details
Published in:PloS one 2021-08, Vol.16 (8), p.e0256050-e0256050
Main Authors: Islam, Mohammad Zohrul, Othman, Mohammad Lutfi, Abdul Wahab, Noor Izzri, Veerasamy, Veerapandiyan, Opu, Saifur Rahman, Inbamani, Abinaya, Annamalai, Vishalakshi
Format: Article
Language:English
Subjects:
Algorithms
Animals
Aquatic Organisms - physiology
Biology and Life Sciences
Brownian motion
Brownian movements
Computer and Information Sciences
Cost analysis
Ecology and Environmental Sciences
Electric Power Supplies - standards
Electric power transmission
Electricity
Energy development
Energy management systems
Energy research
Engineering
Engineering and Technology
Feeding Behavior
Foraging behavior
Genetic algorithms
Heuristic
Heuristic methods
Linear programming
Marine Biology
Mathematical optimization
Models, Biological
Movement
Optimization
Optimization algorithms
Optimization techniques
Physical Sciences
Power
Power flow
Predation (Biology)
Predators
Predatory Behavior
Prey
Reactive power
Research and Analysis Methods
Social Sciences
Supervision
Voltage
Voltage stability
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c692t-f3fd9d42750fe15ab4e6120cd954040b0e4e87729cb3aac12960c367c7193743
cites cdi_FETCH-LOGICAL-c692t-f3fd9d42750fe15ab4e6120cd954040b0e4e87729cb3aac12960c367c7193743
container_end_page e0256050
container_issue 8
container_start_page e0256050
container_title PloS one
container_volume 16
creator Islam, Mohammad Zohrul
Othman, Mohammad Lutfi
Abdul Wahab, Noor Izzri
Veerasamy, Veerapandiyan
Opu, Saifur Rahman
Inbamani, Abinaya
Annamalai, Vishalakshi
description This study presents a nature-inspired, and metaheuristic-based Marine predator algorithm (MPA) for solving the optimal power flow (OPF) problem. The significant insight of MPA is the widespread foraging strategy called the Levy walk and Brownian movements in ocean predators, including the optimal encounter rate policy in biological interaction among predators and prey which make the method to solve the real-world engineering problems of OPF. The OPF problem has been extensively used in power system operation, planning, and management over a long time. In this work, the MPA is analyzed to solve the single-objective OPF problem considering the fuel cost, real and reactive power loss, voltage deviation, and voltage stability enhancement index as objective functions. The proposed method is tested on IEEE 30-bus test system and the obtained results by the proposed method are compared with recent literature studies. The acquired results demonstrate that the proposed method is quite competitive among the nature-inspired optimization techniques reported in the literature.
doi_str_mv 10.1371/journal.pone.0256050
format article
fullrecord <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2560815777</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A671834360</galeid><doaj_id>oai_doaj_org_article_007afd7cb59b4957926866c50665b636</doaj_id><sourcerecordid>A671834360</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-f3fd9d42750fe15ab4e6120cd954040b0e4e87729cb3aac12960c367c7193743</originalsourceid><addsrcrecordid>eNqNkl2L1DAUhoso7rr6D0QLgujFjPlokvZGWBY_RlYWdPE2pOlpJ0Om6Sbprv57MzvdZSp7IYU2pM95k_OeN8teYrTEVOAPGzf6Xtnl4HpYIsI4YuhRdowrShacIPr4YH2UPQthgxCjJedPsyNa0JKWBB9n374rb3rIBw-Nis6HXNnOeRPX27x1Pg_OXpu-y0N6WVi4egM6mmvI3RDNVtl8cDfg89a6m-fZk1bZAC-m70l2-fnT5dnXxfnFl9XZ6flC84rERUvbpmoKIhhqATNVF8AxQbqpWIEKVCMooBSCVLqmSmlMKo405UKL1I4o6En2ei87WBfk5EKQOwNKzIQQiVjticapjRx8uqf_I50y8nbD-U4qH422IBESqm2ErllVFxUTFeHJIc0Q56zmlCetj9NpY72FRkMfvbIz0fmf3qxl565lSdNAOEkC7yYB765GCFFuTdBgrerBjbf3xkUahsAJffMP-nB3E9Wp1IDpW5fO1TtRecoFLtNsOUrU8gEqPQ1sjU6RaU3anxW8nxUkJsLv2KkxBLn6-eP_2Ytfc_btAbsGZeM6hWqMxvVhDhZ7UHsXgof23mSM5C7xd27IXeLllPhU9upwQPdFdxGnfwFKW_nv</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2560815777</pqid></control><display><type>article</type><title>Marine predators algorithm for solving single-objective optimal power flow</title><source>Publicly Available Content Database</source><source>PubMed Central</source><creator>Islam, Mohammad Zohrul ; Othman, Mohammad Lutfi ; Abdul Wahab, Noor Izzri ; Veerasamy, Veerapandiyan ; Opu, Saifur Rahman ; Inbamani, Abinaya ; Annamalai, Vishalakshi</creator><contributor>Arya, Yogendra</contributor><creatorcontrib>Islam, Mohammad Zohrul ; Othman, Mohammad Lutfi ; Abdul Wahab, Noor Izzri ; Veerasamy, Veerapandiyan ; Opu, Saifur Rahman ; Inbamani, Abinaya ; Annamalai, Vishalakshi ; Arya, Yogendra</creatorcontrib><description>This study presents a nature-inspired, and metaheuristic-based Marine predator algorithm (MPA) for solving the optimal power flow (OPF) problem. The significant insight of MPA is the widespread foraging strategy called the Levy walk and Brownian movements in ocean predators, including the optimal encounter rate policy in biological interaction among predators and prey which make the method to solve the real-world engineering problems of OPF. The OPF problem has been extensively used in power system operation, planning, and management over a long time. In this work, the MPA is analyzed to solve the single-objective OPF problem considering the fuel cost, real and reactive power loss, voltage deviation, and voltage stability enhancement index as objective functions. The proposed method is tested on IEEE 30-bus test system and the obtained results by the proposed method are compared with recent literature studies. The acquired results demonstrate that the proposed method is quite competitive among the nature-inspired optimization techniques reported in the literature.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0256050</identifier><identifier>PMID: 34383821</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Animals ; Aquatic Organisms - physiology ; Biology and Life Sciences ; Brownian motion ; Brownian movements ; Computer and Information Sciences ; Cost analysis ; Ecology and Environmental Sciences ; Electric Power Supplies - standards ; Electric power transmission ; Electricity ; Energy development ; Energy management systems ; Energy research ; Engineering ; Engineering and Technology ; Feeding Behavior ; Foraging behavior ; Genetic algorithms ; Heuristic ; Heuristic methods ; Linear programming ; Marine Biology ; Mathematical optimization ; Models, Biological ; Movement ; Optimization ; Optimization algorithms ; Optimization techniques ; Physical Sciences ; Power ; Power flow ; Predation (Biology) ; Predators ; Predatory Behavior ; Prey ; Reactive power ; Research and Analysis Methods ; Social Sciences ; Supervision ; Voltage ; Voltage stability</subject><ispartof>PloS one, 2021-08, Vol.16 (8), p.e0256050-e0256050</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Islam et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Islam et al 2021 Islam et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-f3fd9d42750fe15ab4e6120cd954040b0e4e87729cb3aac12960c367c7193743</citedby><cites>FETCH-LOGICAL-c692t-f3fd9d42750fe15ab4e6120cd954040b0e4e87729cb3aac12960c367c7193743</cites><orcidid>0000-0003-0382-8666 ; 0000-0002-0742-5699</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2560815777/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2560815777?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34383821$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Arya, Yogendra</contributor><creatorcontrib>Islam, Mohammad Zohrul</creatorcontrib><creatorcontrib>Othman, Mohammad Lutfi</creatorcontrib><creatorcontrib>Abdul Wahab, Noor Izzri</creatorcontrib><creatorcontrib>Veerasamy, Veerapandiyan</creatorcontrib><creatorcontrib>Opu, Saifur Rahman</creatorcontrib><creatorcontrib>Inbamani, Abinaya</creatorcontrib><creatorcontrib>Annamalai, Vishalakshi</creatorcontrib><title>Marine predators algorithm for solving single-objective optimal power flow</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>This study presents a nature-inspired, and metaheuristic-based Marine predator algorithm (MPA) for solving the optimal power flow (OPF) problem. The significant insight of MPA is the widespread foraging strategy called the Levy walk and Brownian movements in ocean predators, including the optimal encounter rate policy in biological interaction among predators and prey which make the method to solve the real-world engineering problems of OPF. The OPF problem has been extensively used in power system operation, planning, and management over a long time. In this work, the MPA is analyzed to solve the single-objective OPF problem considering the fuel cost, real and reactive power loss, voltage deviation, and voltage stability enhancement index as objective functions. The proposed method is tested on IEEE 30-bus test system and the obtained results by the proposed method are compared with recent literature studies. The acquired results demonstrate that the proposed method is quite competitive among the nature-inspired optimization techniques reported in the literature.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Aquatic Organisms - physiology</subject><subject>Biology and Life Sciences</subject><subject>Brownian motion</subject><subject>Brownian movements</subject><subject>Computer and Information Sciences</subject><subject>Cost analysis</subject><subject>Ecology and Environmental Sciences</subject><subject>Electric Power Supplies - standards</subject><subject>Electric power transmission</subject><subject>Electricity</subject><subject>Energy development</subject><subject>Energy management systems</subject><subject>Energy research</subject><subject>Engineering</subject><subject>Engineering and Technology</subject><subject>Feeding Behavior</subject><subject>Foraging behavior</subject><subject>Genetic algorithms</subject><subject>Heuristic</subject><subject>Heuristic methods</subject><subject>Linear programming</subject><subject>Marine Biology</subject><subject>Mathematical optimization</subject><subject>Models, Biological</subject><subject>Movement</subject><subject>Optimization</subject><subject>Optimization algorithms</subject><subject>Optimization techniques</subject><subject>Physical Sciences</subject><subject>Power</subject><subject>Power flow</subject><subject>Predation (Biology)</subject><subject>Predators</subject><subject>Predatory Behavior</subject><subject>Prey</subject><subject>Reactive power</subject><subject>Research and Analysis Methods</subject><subject>Social Sciences</subject><subject>Supervision</subject><subject>Voltage</subject><subject>Voltage stability</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNkl2L1DAUhoso7rr6D0QLgujFjPlokvZGWBY_RlYWdPE2pOlpJ0Om6Sbprv57MzvdZSp7IYU2pM95k_OeN8teYrTEVOAPGzf6Xtnl4HpYIsI4YuhRdowrShacIPr4YH2UPQthgxCjJedPsyNa0JKWBB9n374rb3rIBw-Nis6HXNnOeRPX27x1Pg_OXpu-y0N6WVi4egM6mmvI3RDNVtl8cDfg89a6m-fZk1bZAC-m70l2-fnT5dnXxfnFl9XZ6flC84rERUvbpmoKIhhqATNVF8AxQbqpWIEKVCMooBSCVLqmSmlMKo405UKL1I4o6En2ei87WBfk5EKQOwNKzIQQiVjticapjRx8uqf_I50y8nbD-U4qH422IBESqm2ErllVFxUTFeHJIc0Q56zmlCetj9NpY72FRkMfvbIz0fmf3qxl565lSdNAOEkC7yYB765GCFFuTdBgrerBjbf3xkUahsAJffMP-nB3E9Wp1IDpW5fO1TtRecoFLtNsOUrU8gEqPQ1sjU6RaU3anxW8nxUkJsLv2KkxBLn6-eP_2Ytfc_btAbsGZeM6hWqMxvVhDhZ7UHsXgof23mSM5C7xd27IXeLllPhU9upwQPdFdxGnfwFKW_nv</recordid><startdate>20210812</startdate><enddate>20210812</enddate><creator>Islam, Mohammad Zohrul</creator><creator>Othman, Mohammad Lutfi</creator><creator>Abdul Wahab, Noor Izzri</creator><creator>Veerasamy, Veerapandiyan</creator><creator>Opu, Saifur Rahman</creator><creator>Inbamani, Abinaya</creator><creator>Annamalai, Vishalakshi</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-0382-8666</orcidid><orcidid>https://orcid.org/0000-0002-0742-5699</orcidid></search><sort><creationdate>20210812</creationdate><title>Marine predators algorithm for solving single-objective optimal power flow</title><author>Islam, Mohammad Zohrul ; Othman, Mohammad Lutfi ; Abdul Wahab, Noor Izzri ; Veerasamy, Veerapandiyan ; Opu, Saifur Rahman ; Inbamani, Abinaya ; Annamalai, Vishalakshi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-f3fd9d42750fe15ab4e6120cd954040b0e4e87729cb3aac12960c367c7193743</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Aquatic Organisms - physiology</topic><topic>Biology and Life Sciences</topic><topic>Brownian motion</topic><topic>Brownian movements</topic><topic>Computer and Information Sciences</topic><topic>Cost analysis</topic><topic>Ecology and Environmental Sciences</topic><topic>Electric Power Supplies - standards</topic><topic>Electric power transmission</topic><topic>Electricity</topic><topic>Energy development</topic><topic>Energy management systems</topic><topic>Energy research</topic><topic>Engineering</topic><topic>Engineering and Technology</topic><topic>Feeding Behavior</topic><topic>Foraging behavior</topic><topic>Genetic algorithms</topic><topic>Heuristic</topic><topic>Heuristic methods</topic><topic>Linear programming</topic><topic>Marine Biology</topic><topic>Mathematical optimization</topic><topic>Models, Biological</topic><topic>Movement</topic><topic>Optimization</topic><topic>Optimization algorithms</topic><topic>Optimization techniques</topic><topic>Physical Sciences</topic><topic>Power</topic><topic>Power flow</topic><topic>Predation (Biology)</topic><topic>Predators</topic><topic>Predatory Behavior</topic><topic>Prey</topic><topic>Reactive power</topic><topic>Research and Analysis Methods</topic><topic>Social Sciences</topic><topic>Supervision</topic><topic>Voltage</topic><topic>Voltage stability</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Islam, Mohammad Zohrul</creatorcontrib><creatorcontrib>Othman, Mohammad Lutfi</creatorcontrib><creatorcontrib>Abdul Wahab, Noor Izzri</creatorcontrib><creatorcontrib>Veerasamy, Veerapandiyan</creatorcontrib><creatorcontrib>Opu, Saifur Rahman</creatorcontrib><creatorcontrib>Inbamani, Abinaya</creatorcontrib><creatorcontrib>Annamalai, Vishalakshi</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing &amp; Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agriculture Science Database</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>ProQuest Biological Science Journals</collection><collection>Engineering Database</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>ProQuest advanced technologies &amp; aerospace journals</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials science collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Islam, Mohammad Zohrul</au><au>Othman, Mohammad Lutfi</au><au>Abdul Wahab, Noor Izzri</au><au>Veerasamy, Veerapandiyan</au><au>Opu, Saifur Rahman</au><au>Inbamani, Abinaya</au><au>Annamalai, Vishalakshi</au><au>Arya, Yogendra</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Marine predators algorithm for solving single-objective optimal power flow</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2021-08-12</date><risdate>2021</risdate><volume>16</volume><issue>8</issue><spage>e0256050</spage><epage>e0256050</epage><pages>e0256050-e0256050</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>This study presents a nature-inspired, and metaheuristic-based Marine predator algorithm (MPA) for solving the optimal power flow (OPF) problem. The significant insight of MPA is the widespread foraging strategy called the Levy walk and Brownian movements in ocean predators, including the optimal encounter rate policy in biological interaction among predators and prey which make the method to solve the real-world engineering problems of OPF. The OPF problem has been extensively used in power system operation, planning, and management over a long time. In this work, the MPA is analyzed to solve the single-objective OPF problem considering the fuel cost, real and reactive power loss, voltage deviation, and voltage stability enhancement index as objective functions. The proposed method is tested on IEEE 30-bus test system and the obtained results by the proposed method are compared with recent literature studies. The acquired results demonstrate that the proposed method is quite competitive among the nature-inspired optimization techniques reported in the literature.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>34383821</pmid><doi>10.1371/journal.pone.0256050</doi><tpages>e0256050</tpages><orcidid>https://orcid.org/0000-0003-0382-8666</orcidid><orcidid>https://orcid.org/0000-0002-0742-5699</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1932-6203
ispartof PloS one, 2021-08, Vol.16 (8), p.e0256050-e0256050
issn 1932-6203
1932-6203
language eng
recordid cdi_plos_journals_2560815777
source Publicly Available Content Database; PubMed Central
subjects Algorithms
Animals
Aquatic Organisms - physiology
Biology and Life Sciences
Brownian motion
Brownian movements
Computer and Information Sciences
Cost analysis
Ecology and Environmental Sciences
Electric Power Supplies - standards
Electric power transmission
Electricity
Energy development
Energy management systems
Energy research
Engineering
Engineering and Technology
Feeding Behavior
Foraging behavior
Genetic algorithms
Heuristic
Heuristic methods
Linear programming
Marine Biology
Mathematical optimization
Models, Biological
Movement
Optimization
Optimization algorithms
Optimization techniques
Physical Sciences
Power
Power flow
Predation (Biology)
Predators
Predatory Behavior
Prey
Reactive power
Research and Analysis Methods
Social Sciences
Supervision
Voltage
Voltage stability
title Marine predators algorithm for solving single-objective optimal power flow
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T16%3A36%3A51IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Marine%20predators%20algorithm%20for%20solving%20single-objective%20optimal%20power%20flow&rft.jtitle=PloS%20one&rft.au=Islam,%20Mohammad%20Zohrul&rft.date=2021-08-12&rft.volume=16&rft.issue=8&rft.spage=e0256050&rft.epage=e0256050&rft.pages=e0256050-e0256050&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0256050&rft_dat=%3Cgale_plos_%3EA671834360%3C/gale_plos_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c692t-f3fd9d42750fe15ab4e6120cd954040b0e4e87729cb3aac12960c367c7193743%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2560815777&rft_id=info:pmid/34383821&rft_galeid=A671834360&rfr_iscdi=true