Loading…
A Hybrid Evolutionary-Based MPPT for Photovoltaic Systems Under Partial Shading Conditions
Under partial shading conditions (PSCs), photovoltaic (PV) system characteristics vary and may have multiple power peaks. Conventional maximum power point tracking (MPPT) methods are unable to track the global peak. In addition, it takes a considerable time to reach the maximum power point (MPP). To...
Saved in:
Published in: | IEEE access 2020, Vol.8, p.38481-38492 |
---|---|
Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
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-c408t-73566cc69f034ab69b1efbc5568bc405e5f0e152f87c58ddbd04b1a85226480b3 |
---|---|
cites | cdi_FETCH-LOGICAL-c408t-73566cc69f034ab69b1efbc5568bc405e5f0e152f87c58ddbd04b1a85226480b3 |
container_end_page | 38492 |
container_issue | |
container_start_page | 38481 |
container_title | IEEE access |
container_volume | 8 |
creator | Joisher, Mansi Singh, Dharampal Taheri, Shamsodin Espinoza-Trejo, Diego R. Pouresmaeil, Edris Taheri, Hamed |
description | Under partial shading conditions (PSCs), photovoltaic (PV) system characteristics vary and may have multiple power peaks. Conventional maximum power point tracking (MPPT) methods are unable to track the global peak. In addition, it takes a considerable time to reach the maximum power point (MPP). To address these issues, this paper proposes an improved hybrid MPPT method using the conventional evolutional algorithms, i.e., Particle Swarm Optimization (PSO) and Differential Evaluation (DE). The main feature of the proposed hybrid MPPT method is the advantage of one method compensates for shortcomings of the other method. Furthermore, the algorithm is simple and rapid. It can be easily implemented on a low-cost microcontroller. To evaluate the performance of the proposed method, MATLAB simulations are carried out under different PSCc. Experimental verifications are conducted using a boost converter setup, an ET-M53695 panel and a TMS320F28335 DSP. Finally, the simulation and hardware results are compared to those from the PSO and DE methods. The superiority of the hybrid method over PSO and DE methods is highlighted through the results. |
doi_str_mv | 10.1109/ACCESS.2020.2975742 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1109_ACCESS_2020_2975742</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9006783</ieee_id><doaj_id>oai_doaj_org_article_5332fab575cc484bad06fde78771313b</doaj_id><sourcerecordid>2454757481</sourcerecordid><originalsourceid>FETCH-LOGICAL-c408t-73566cc69f034ab69b1efbc5568bc405e5f0e152f87c58ddbd04b1a85226480b3</originalsourceid><addsrcrecordid>eNpNUU1LJDEUbGQXFPUXeAl47tl8J30cm3FHUHZg9LKXkE_NMHY06VmYf2_aFtl3yaNeVeUl1TRXCC4Qgt2vZd-vttsFhhgucCeYoPikOcOIdy1hhP_4rz9tLkvZwVqyQkycNX-XYH00OTqw-pf2hzGmQedje6OLd-Bhs3kEIWWweUljqvNRRwu2xzL61wKeBufrSOcx6j3YvmgXh2fQp8HFyaZcND-D3hd_-XWeN0-3q8d-3d7_-X3XL-9bS6EcW0EY59byLkBCteGdQT4YyxiXpjKYZwF6xHCQwjLpnHGQGqQlw5hTCQ05b-5mX5f0Tr3l-FpfoJKO6hNI-VlNO9q9V4wQHLRhgllLJTXaQR6cF1IIRBCZvK5nr7ec3g--jGqXDnmo6ytMGZ0-V6LKIjPL5lRK9uH7VgTVlImaM1FTJuork6q6mlXRe_-t6CDkQhLyAez4hy8</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2454757481</pqid></control><display><type>article</type><title>A Hybrid Evolutionary-Based MPPT for Photovoltaic Systems Under Partial Shading Conditions</title><source>IEEE Open Access Journals</source><creator>Joisher, Mansi ; Singh, Dharampal ; Taheri, Shamsodin ; Espinoza-Trejo, Diego R. ; Pouresmaeil, Edris ; Taheri, Hamed</creator><creatorcontrib>Joisher, Mansi ; Singh, Dharampal ; Taheri, Shamsodin ; Espinoza-Trejo, Diego R. ; Pouresmaeil, Edris ; Taheri, Hamed</creatorcontrib><description>Under partial shading conditions (PSCs), photovoltaic (PV) system characteristics vary and may have multiple power peaks. Conventional maximum power point tracking (MPPT) methods are unable to track the global peak. In addition, it takes a considerable time to reach the maximum power point (MPP). To address these issues, this paper proposes an improved hybrid MPPT method using the conventional evolutional algorithms, i.e., Particle Swarm Optimization (PSO) and Differential Evaluation (DE). The main feature of the proposed hybrid MPPT method is the advantage of one method compensates for shortcomings of the other method. Furthermore, the algorithm is simple and rapid. It can be easily implemented on a low-cost microcontroller. To evaluate the performance of the proposed method, MATLAB simulations are carried out under different PSCc. Experimental verifications are conducted using a boost converter setup, an ET-M53695 panel and a TMS320F28335 DSP. Finally, the simulation and hardware results are compared to those from the PSO and DE methods. The superiority of the hybrid method over PSO and DE methods is highlighted through the results.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2020.2975742</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Algorithms ; Convergence ; Converters ; differential evaluation ; Maximum power point trackers ; maximum power point tracking ; Maximum power tracking ; Microcontrollers ; Optimization ; partial shading condition ; Particle swarm optimization ; Performance evaluation ; Photovoltaic cells ; Photovoltaic systems ; Shading ; Sociology ; Statistics</subject><ispartof>IEEE access, 2020, Vol.8, p.38481-38492</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-73566cc69f034ab69b1efbc5568bc405e5f0e152f87c58ddbd04b1a85226480b3</citedby><cites>FETCH-LOGICAL-c408t-73566cc69f034ab69b1efbc5568bc405e5f0e152f87c58ddbd04b1a85226480b3</cites><orcidid>0000-0002-2079-064X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9006783$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,4024,27633,27923,27924,27925,54933</link.rule.ids></links><search><creatorcontrib>Joisher, Mansi</creatorcontrib><creatorcontrib>Singh, Dharampal</creatorcontrib><creatorcontrib>Taheri, Shamsodin</creatorcontrib><creatorcontrib>Espinoza-Trejo, Diego R.</creatorcontrib><creatorcontrib>Pouresmaeil, Edris</creatorcontrib><creatorcontrib>Taheri, Hamed</creatorcontrib><title>A Hybrid Evolutionary-Based MPPT for Photovoltaic Systems Under Partial Shading Conditions</title><title>IEEE access</title><addtitle>Access</addtitle><description>Under partial shading conditions (PSCs), photovoltaic (PV) system characteristics vary and may have multiple power peaks. Conventional maximum power point tracking (MPPT) methods are unable to track the global peak. In addition, it takes a considerable time to reach the maximum power point (MPP). To address these issues, this paper proposes an improved hybrid MPPT method using the conventional evolutional algorithms, i.e., Particle Swarm Optimization (PSO) and Differential Evaluation (DE). The main feature of the proposed hybrid MPPT method is the advantage of one method compensates for shortcomings of the other method. Furthermore, the algorithm is simple and rapid. It can be easily implemented on a low-cost microcontroller. To evaluate the performance of the proposed method, MATLAB simulations are carried out under different PSCc. Experimental verifications are conducted using a boost converter setup, an ET-M53695 panel and a TMS320F28335 DSP. Finally, the simulation and hardware results are compared to those from the PSO and DE methods. The superiority of the hybrid method over PSO and DE methods is highlighted through the results.</description><subject>Algorithms</subject><subject>Convergence</subject><subject>Converters</subject><subject>differential evaluation</subject><subject>Maximum power point trackers</subject><subject>maximum power point tracking</subject><subject>Maximum power tracking</subject><subject>Microcontrollers</subject><subject>Optimization</subject><subject>partial shading condition</subject><subject>Particle swarm optimization</subject><subject>Performance evaluation</subject><subject>Photovoltaic cells</subject><subject>Photovoltaic systems</subject><subject>Shading</subject><subject>Sociology</subject><subject>Statistics</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1LJDEUbGQXFPUXeAl47tl8J30cm3FHUHZg9LKXkE_NMHY06VmYf2_aFtl3yaNeVeUl1TRXCC4Qgt2vZd-vttsFhhgucCeYoPikOcOIdy1hhP_4rz9tLkvZwVqyQkycNX-XYH00OTqw-pf2hzGmQedje6OLd-Bhs3kEIWWweUljqvNRRwu2xzL61wKeBufrSOcx6j3YvmgXh2fQp8HFyaZcND-D3hd_-XWeN0-3q8d-3d7_-X3XL-9bS6EcW0EY59byLkBCteGdQT4YyxiXpjKYZwF6xHCQwjLpnHGQGqQlw5hTCQ05b-5mX5f0Tr3l-FpfoJKO6hNI-VlNO9q9V4wQHLRhgllLJTXaQR6cF1IIRBCZvK5nr7ec3g--jGqXDnmo6ytMGZ0-V6LKIjPL5lRK9uH7VgTVlImaM1FTJuork6q6mlXRe_-t6CDkQhLyAez4hy8</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Joisher, Mansi</creator><creator>Singh, Dharampal</creator><creator>Taheri, Shamsodin</creator><creator>Espinoza-Trejo, Diego R.</creator><creator>Pouresmaeil, Edris</creator><creator>Taheri, Hamed</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-2079-064X</orcidid></search><sort><creationdate>2020</creationdate><title>A Hybrid Evolutionary-Based MPPT for Photovoltaic Systems Under Partial Shading Conditions</title><author>Joisher, Mansi ; Singh, Dharampal ; Taheri, Shamsodin ; Espinoza-Trejo, Diego R. ; Pouresmaeil, Edris ; Taheri, Hamed</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-73566cc69f034ab69b1efbc5568bc405e5f0e152f87c58ddbd04b1a85226480b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Convergence</topic><topic>Converters</topic><topic>differential evaluation</topic><topic>Maximum power point trackers</topic><topic>maximum power point tracking</topic><topic>Maximum power tracking</topic><topic>Microcontrollers</topic><topic>Optimization</topic><topic>partial shading condition</topic><topic>Particle swarm optimization</topic><topic>Performance evaluation</topic><topic>Photovoltaic cells</topic><topic>Photovoltaic systems</topic><topic>Shading</topic><topic>Sociology</topic><topic>Statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Joisher, Mansi</creatorcontrib><creatorcontrib>Singh, Dharampal</creatorcontrib><creatorcontrib>Taheri, Shamsodin</creatorcontrib><creatorcontrib>Espinoza-Trejo, Diego R.</creatorcontrib><creatorcontrib>Pouresmaeil, Edris</creatorcontrib><creatorcontrib>Taheri, Hamed</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Xplore</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Joisher, Mansi</au><au>Singh, Dharampal</au><au>Taheri, Shamsodin</au><au>Espinoza-Trejo, Diego R.</au><au>Pouresmaeil, Edris</au><au>Taheri, Hamed</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Hybrid Evolutionary-Based MPPT for Photovoltaic Systems Under Partial Shading Conditions</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2020</date><risdate>2020</risdate><volume>8</volume><spage>38481</spage><epage>38492</epage><pages>38481-38492</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>Under partial shading conditions (PSCs), photovoltaic (PV) system characteristics vary and may have multiple power peaks. Conventional maximum power point tracking (MPPT) methods are unable to track the global peak. In addition, it takes a considerable time to reach the maximum power point (MPP). To address these issues, this paper proposes an improved hybrid MPPT method using the conventional evolutional algorithms, i.e., Particle Swarm Optimization (PSO) and Differential Evaluation (DE). The main feature of the proposed hybrid MPPT method is the advantage of one method compensates for shortcomings of the other method. Furthermore, the algorithm is simple and rapid. It can be easily implemented on a low-cost microcontroller. To evaluate the performance of the proposed method, MATLAB simulations are carried out under different PSCc. Experimental verifications are conducted using a boost converter setup, an ET-M53695 panel and a TMS320F28335 DSP. Finally, the simulation and hardware results are compared to those from the PSO and DE methods. The superiority of the hybrid method over PSO and DE methods is highlighted through the results.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2020.2975742</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-2079-064X</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2169-3536 |
ispartof | IEEE access, 2020, Vol.8, p.38481-38492 |
issn | 2169-3536 2169-3536 |
language | eng |
recordid | cdi_crossref_primary_10_1109_ACCESS_2020_2975742 |
source | IEEE Open Access Journals |
subjects | Algorithms Convergence Converters differential evaluation Maximum power point trackers maximum power point tracking Maximum power tracking Microcontrollers Optimization partial shading condition Particle swarm optimization Performance evaluation Photovoltaic cells Photovoltaic systems Shading Sociology Statistics |
title | A Hybrid Evolutionary-Based MPPT for Photovoltaic Systems Under Partial Shading Conditions |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T05%3A17%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Hybrid%20Evolutionary-Based%20MPPT%20for%20Photovoltaic%20Systems%20Under%20Partial%20Shading%20Conditions&rft.jtitle=IEEE%20access&rft.au=Joisher,%20Mansi&rft.date=2020&rft.volume=8&rft.spage=38481&rft.epage=38492&rft.pages=38481-38492&rft.issn=2169-3536&rft.eissn=2169-3536&rft.coden=IAECCG&rft_id=info:doi/10.1109/ACCESS.2020.2975742&rft_dat=%3Cproquest_cross%3E2454757481%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c408t-73566cc69f034ab69b1efbc5568bc405e5f0e152f87c58ddbd04b1a85226480b3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2454757481&rft_id=info:pmid/&rft_ieee_id=9006783&rfr_iscdi=true |