Collaborative swarm intelligence to estimate PV parameters

•Collaborative swarm intelligence is proposed to estimate PV parameters.•The proposed methodology mitigates premature convergence and population stagnation.•Benchmark functions and experimental data are used to test the new methodology.•The new methodology determines reliable solutions quickly and a...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Energy conversion and management Ročník 185; s. 866 - 890
Hlavní autoři:	Nunes, H.G.G., Pombo, J.A.N., Bento, P.M.R., Mariano, S.J.P.S., Calado, M.R.A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 01.04.2019 Elsevier Science Ltd
Témata:	case studies Circuits Collaborative swarm intelligence Computer applications Data processing Double-diode model electronic circuits Hybrid metaheuristic Intelligence Mathematical models Methodology Optimization Parameter estimation Photovoltaic cells Photovoltaics shade Shading Single-diode model Solar cells Stagnation Swarm intelligence system optimization Double-diode model Collaborative swarm intelligence Parameter estimation Single-diode model Hybrid metaheuristic
ISSN:	0196-8904, 1879-2227
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	•Collaborative swarm intelligence is proposed to estimate PV parameters.•The proposed methodology mitigates premature convergence and population stagnation.•Benchmark functions and experimental data are used to test the new methodology.•The new methodology determines reliable solutions quickly and accurately.•Several comparisons and metrics support the obtained results. To properly evaluate, control and optimize photovoltaic (PV) systems, it is crucial to accurately estimate the equivalent electric circuit parameters from the respective mathematical models that characterize the PV cells or modules behavior. This is currently a hot research topic that has attracted the attention of numerous researchers. In this paper, we propose a new hybrid methodology that combines diversification and intensification mechanisms from different metaheuristics (MHs) to estimate PV parameters precisely. The proposed methodology has the capacity to adapt to the specific optimization problem and maintain diversity when building solutions, thus mitigating premature convergence and population stagnation. This methodology can incorporate several MHs (two or more swarms) with different potentialities, enabling a good balance between diversification and intensification mechanisms. Furthermore, it is able to explore a multidimensional search space in different regions simultaneously. To validate its performance, the proposed methodology was compared with other well-established MHs in several benchmark functions, and used to estimate PV parameters in single and double-diode models in two case studies, the first using standard literature data, and the second using measured data from a real application with and without the occurrence of partial shading. The proposed methodology was able to find highly accurate solutions with reduced computational cost and high reliability. Comparisons with the other MHs demonstrate that the proposed methodology presents a very competitive performance when solving the PV parameter estimation problem.
AbstractList	To properly evaluate, control and optimize photovoltaic (PV) systems, it is crucial to accurately estimate the equivalent electric circuit parameters from the respective mathematical models that characterize the PV cells or modules behavior. This is currently a hot research topic that has attracted the attention of numerous researchers. In this paper, we propose a new hybrid methodology that combines diversification and intensification mechanisms from different metaheuristics (MHs) to estimate PV parameters precisely. The proposed methodology has the capacity to adapt to the specific optimization problem and maintain diversity when building solutions, thus mitigating premature convergence and population stagnation. This methodology can incorporate several MHs (two or more swarms) with different potentialities, enabling a good balance between diversification and intensification mechanisms. Furthermore, it is able to explore a multidimensional search space in different regions simultaneously. To validate its performance, the proposed methodology was compared with other well-established MHs in several benchmark functions, and used to estimate PV parameters in single and double-diode models in two case studies, the first using standard literature data, and the second using measured data from a real application with and without the occurrence of partial shading. The proposed methodology was able to find highly accurate solutions with reduced computational cost and high reliability. Comparisons with the other MHs demonstrate that the proposed methodology presents a very competitive performance when solving the PV parameter estimation problem. •Collaborative swarm intelligence is proposed to estimate PV parameters.•The proposed methodology mitigates premature convergence and population stagnation.•Benchmark functions and experimental data are used to test the new methodology.•The new methodology determines reliable solutions quickly and accurately.•Several comparisons and metrics support the obtained results. To properly evaluate, control and optimize photovoltaic (PV) systems, it is crucial to accurately estimate the equivalent electric circuit parameters from the respective mathematical models that characterize the PV cells or modules behavior. This is currently a hot research topic that has attracted the attention of numerous researchers. In this paper, we propose a new hybrid methodology that combines diversification and intensification mechanisms from different metaheuristics (MHs) to estimate PV parameters precisely. The proposed methodology has the capacity to adapt to the specific optimization problem and maintain diversity when building solutions, thus mitigating premature convergence and population stagnation. This methodology can incorporate several MHs (two or more swarms) with different potentialities, enabling a good balance between diversification and intensification mechanisms. Furthermore, it is able to explore a multidimensional search space in different regions simultaneously. To validate its performance, the proposed methodology was compared with other well-established MHs in several benchmark functions, and used to estimate PV parameters in single and double-diode models in two case studies, the first using standard literature data, and the second using measured data from a real application with and without the occurrence of partial shading. The proposed methodology was able to find highly accurate solutions with reduced computational cost and high reliability. Comparisons with the other MHs demonstrate that the proposed methodology presents a very competitive performance when solving the PV parameter estimation problem.
Author	Calado, M.R.A. Pombo, J.A.N. Mariano, S.J.P.S. Bento, P.M.R. Nunes, H.G.G.
Author_xml	– sequence: 1 givenname: H.G.G. orcidid: 0000-0002-6029-7032 surname: Nunes fullname: Nunes, H.G.G. email: hugo.nunes@ubi.pt organization: Department of Electromechanical Engineering, University of Beira Interior, Covilhã 6201-001, Portugal – sequence: 2 givenname: J.A.N. surname: Pombo fullname: Pombo, J.A.N. email: jose.pombo@ubi.pt organization: Department of Electromechanical Engineering, University of Beira Interior, Covilhã 6201-001, Portugal – sequence: 3 givenname: P.M.R. surname: Bento fullname: Bento, P.M.R. email: pedro.bento@ubi.pt organization: Department of Electromechanical Engineering, University of Beira Interior, Covilhã 6201-001, Portugal – sequence: 4 givenname: S.J.P.S. surname: Mariano fullname: Mariano, S.J.P.S. email: sm@ubi.pt organization: Department of Electromechanical Engineering, University of Beira Interior, Covilhã 6201-001, Portugal – sequence: 5 givenname: M.R.A. surname: Calado fullname: Calado, M.R.A. email: rc@ubi.pt organization: Department of Electromechanical Engineering, University of Beira Interior, Covilhã 6201-001, Portugal
BookMark	eNqFkEtLAzEUhYNUsK3-BRlw42bGZDKPjLhQii8o6KK4DbeZjKTMJDVJK_57b6luuukqi3zncO43ISPrrCbkktGMUVbdrDJtlbMD2CynrMlonlHKT8iYibpJ8zyvR2SMH1UqGlqckUkIK4pESasxuZ25voel8xDNVifhG_yQGBt135tP7NVJdIkO0QwQdfL-kazBw6Cj9uGcnHbQB33x907J4ulxMXtJ52_Pr7OHeaqKkseULZdNyUFAQ7uqBSgZcCEEVwLqNlcgupYrxZhiLW-pFpwVtFuWrMMcqxSfkut97dq7rw1OkYMJCveB1W4TJB5IRUGLWiB6dYCu3MZbHIcUw-KqLGqkqj2lvAvB606uPZ7nfySjcmdUruS_UbkzKmku0RcG7w6CykT05mz0YPrj8ft9XKOsrdFeBmV2ilvjtYqydeZYxS_ePZiw
CitedBy_id	crossref_primary_10_1016_j_solener_2020_09_047 crossref_primary_10_1016_j_enconman_2019_112450 crossref_primary_10_3390_su15010509 crossref_primary_10_1016_j_enconman_2019_05_057 crossref_primary_10_1155_2024_9777345 crossref_primary_10_1016_j_egyr_2022_03_144 crossref_primary_10_1007_s42835_020_00589_1 crossref_primary_10_1016_j_asoc_2024_112221 crossref_primary_10_1016_j_egyr_2023_03_105 crossref_primary_10_1016_j_solener_2022_08_004 crossref_primary_10_1016_j_enconman_2020_112990 crossref_primary_10_1016_j_egyr_2023_05_221 crossref_primary_10_3390_en17071716 crossref_primary_10_1016_j_renene_2025_123427 crossref_primary_10_1016_j_egyr_2022_11_171 crossref_primary_10_1016_j_solener_2020_10_062 crossref_primary_10_1016_j_egyr_2022_11_092 crossref_primary_10_1007_s00500_020_05227_6 crossref_primary_10_1016_j_enconman_2020_112716 crossref_primary_10_1016_j_enconman_2020_113409 crossref_primary_10_1080_02522667_2021_1960545 crossref_primary_10_1016_j_enconman_2019_111870 crossref_primary_10_1016_j_seta_2020_100849 crossref_primary_10_1109_ACCESS_2025_3546986 crossref_primary_10_1016_j_asoc_2024_112295 crossref_primary_10_1109_ACCESS_2021_3069748 crossref_primary_10_3390_en15197212 crossref_primary_10_1016_j_solener_2020_02_068 crossref_primary_10_1016_j_sciaf_2023_e01706 crossref_primary_10_22395_rium_v21n40a2 crossref_primary_10_1016_j_egyr_2021_01_024 crossref_primary_10_1038_s41598_025_85115_x crossref_primary_10_1007_s10825_024_02205_1 crossref_primary_10_1016_j_asoc_2025_113117 crossref_primary_10_1016_j_heliyon_2021_e06673 crossref_primary_10_3390_en14112980 crossref_primary_10_1155_2019_3923691 crossref_primary_10_1007_s00202_024_02885_9 crossref_primary_10_1007_s10825_020_01617_z crossref_primary_10_3390_s22186989 crossref_primary_10_1016_j_heliyon_2024_e38412 crossref_primary_10_1049_rpg2_12262 crossref_primary_10_1007_s10825_021_01812_6 crossref_primary_10_1007_s42235_024_00479_6 crossref_primary_10_1155_2019_4692108 crossref_primary_10_1016_j_seta_2022_102582 crossref_primary_10_1007_s00521_022_07047_1 crossref_primary_10_1016_j_enconman_2023_117621 crossref_primary_10_3390_en17102284 crossref_primary_10_1016_j_ijleo_2021_167973 crossref_primary_10_1007_s42341_021_00312_5 crossref_primary_10_1155_2020_6669579 crossref_primary_10_3390_batteries8020018 crossref_primary_10_1007_s00521_021_05822_0 crossref_primary_10_1016_j_enconman_2020_112764 crossref_primary_10_1109_ACCESS_2020_3005236 crossref_primary_10_1002_oca_2984 crossref_primary_10_1007_s11227_024_06899_9 crossref_primary_10_1007_s00521_023_08451_x crossref_primary_10_1016_j_enconman_2020_113388 crossref_primary_10_1016_j_enconman_2020_113784 crossref_primary_10_1016_j_ijleo_2022_168873 crossref_primary_10_1109_ACCESS_2020_3000770 crossref_primary_10_1002_jnm_3163 crossref_primary_10_1016_j_engappai_2021_104608 crossref_primary_10_3390_sym14081569 crossref_primary_10_1002_er_5756 crossref_primary_10_1049_rpg2_12712 crossref_primary_10_1002_er_5747 crossref_primary_10_1016_j_solener_2020_06_100 crossref_primary_10_1016_j_enconman_2020_113820 crossref_primary_10_1016_j_rser_2022_112436 crossref_primary_10_1109_ACCESS_2022_3142779 crossref_primary_10_1016_j_isatra_2021_01_045 crossref_primary_10_1016_j_egyr_2022_05_011 crossref_primary_10_1016_j_renene_2024_120507 crossref_primary_10_1016_j_enconman_2020_113279 crossref_primary_10_1016_j_solener_2020_02_093 crossref_primary_10_1038_s41598_025_86063_2 crossref_primary_10_3390_electronics10040472 crossref_primary_10_1016_j_enconman_2020_113395 crossref_primary_10_1109_ACCESS_2021_3103146 crossref_primary_10_1016_j_energy_2021_120136 crossref_primary_10_1016_j_renene_2021_04_103 crossref_primary_10_1108_COMPEL_09_2022_0306 crossref_primary_10_1016_j_asoc_2021_108357
Cites_doi	10.1016/j.enconman.2016.09.085 10.1016/j.enconman.2018.08.053 10.1016/j.enconman.2017.04.054 10.1109/T-ED.1987.22920 10.1016/j.solener.2016.08.056 10.1016/j.apenergy.2017.12.115 10.1016/j.enconman.2016.12.082 10.1016/j.swevo.2017.02.005 10.1016/j.apenergy.2018.06.010 10.1016/j.enconman.2016.09.005 10.1016/j.enconman.2018.05.062 10.1016/j.solener.2014.02.014 10.1016/j.solener.2017.10.063 10.1016/j.renene.2017.04.014 10.1016/j.swevo.2018.01.009 10.1007/s40095-015-0198-5 10.1016/j.solmat.2010.09.023 10.1049/ip-epa:19990116 10.1016/j.energy.2016.01.052 10.1109/4235.771163 10.3390/en10070865 10.3390/en8087563 10.1016/j.renene.2018.09.017 10.1016/j.enconman.2017.04.042 10.3390/en10081213 10.1016/j.solener.2017.01.064 10.1016/j.enconman.2018.05.035 10.1016/j.ijhydene.2013.12.110 10.3390/app8030339 10.1016/j.apenergy.2015.05.035 10.1016/j.solener.2016.03.033 10.1016/j.advengsoft.2016.01.008 10.1016/j.solener.2017.08.006 10.1016/j.enconman.2017.08.063 10.1016/j.apenergy.2018.09.161 10.3390/en11051060 10.1063/1.4822054 10.1109/TIE.2018.2793216 10.1109/4235.585893 10.1016/j.enconman.2017.12.033 10.1109/TPEL.2009.2013862 10.1016/j.rser.2018.03.011 10.1016/j.asoc.2018.02.037 10.1016/j.asoc.2018.06.025 10.1016/j.rser.2016.03.049 10.1016/j.solener.2014.09.043 10.1016/j.enconman.2018.06.106 10.1016/j.asoc.2018.02.025 10.1016/j.solener.2018.10.050 10.1016/j.rser.2014.01.027 10.1016/j.enconman.2014.06.026 10.1016/j.solener.2018.06.092 10.1016/j.apenergy.2016.08.083 10.1016/j.apenergy.2017.11.078 10.3390/en6010128 10.3390/app8112155 10.1016/j.apenergy.2017.05.029 10.1016/j.solener.2013.05.007 10.1109/TIE.2015.2390193 10.1080/01425918608909835 10.1109/TIE.2016.2615590 10.3390/en10071052
ContentType	Journal Article
Copyright	2019 Elsevier Ltd Copyright Elsevier Science Ltd. Apr 1, 2019
Copyright_xml	– notice: 2019 Elsevier Ltd – notice: Copyright Elsevier Science Ltd. Apr 1, 2019
DBID	AAYXX CITATION 7ST 7TB 8FD C1K FR3 H8D KR7 L7M SOI 7S9 L.6
DOI	10.1016/j.enconman.2019.02.003
DatabaseName	CrossRef Environment Abstracts Mechanical & Transportation Engineering Abstracts Technology Research Database Environmental Sciences and Pollution Management Engineering Research Database Aerospace Database Civil Engineering Abstracts Advanced Technologies Database with Aerospace Environment Abstracts AGRICOLA AGRICOLA - Academic
DatabaseTitle	CrossRef Aerospace Database Civil Engineering Abstracts Technology Research Database Mechanical & Transportation Engineering Abstracts Engineering Research Database Environment Abstracts Advanced Technologies Database with Aerospace Environmental Sciences and Pollution Management AGRICOLA AGRICOLA - Academic
DatabaseTitleList	Aerospace Database AGRICOLA
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	1879-2227
EndPage	890
ExternalDocumentID	10_1016_j_enconman_2019_02_003 S0196890419301566
GroupedDBID	--K --M .DC .~1 0R~ 1B1 1~. 1~5 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN AABNK AACTN AAEDT AAEDW AAHCO AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AARJD AAXUO ABFNM ABFRF ABJNI ABMAC ABYKQ ACBEA ACDAQ ACGFO ACGFS ACIWK ACNCT ACRLP ADBBV ADEZE AEBSH AEFWE AEKER AENEX AFKWA AFRAH AFTJW AGHFR AGUBO AGYEJ AHHHB AHIDL AHJVU AIEXJ AIKHN AITUG AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AXJTR BELTK BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 FDB FIRID FNPLU FYGXN G-Q GBLVA IHE J1W JARJE KOM LY6 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 RIG ROL RPZ SDF SDG SDP SES SPC SPCBC SSR SST SSZ T5K TN5 XPP ZMT ~02 ~G- 29G 6TJ 8WZ 9DU A6W AAHBH AAQXK AATTM AAXKI AAYWO AAYXX ABDPE ABWVN ABXDB ACLOT ACNNM ACRPL ACVFH ADCNI ADMUD ADNMO AEIPS AEUPX AFFNX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP ASPBG AVWKF AZFZN CITATION EFKBS FEDTE FGOYB G-2 HVGLF HZ~ H~9 R2- SAC SEW WUQ ~HD 7ST 7TB 8FD AGCQF C1K FR3 H8D KR7 L7M SOI 7S9 L.6
ID	FETCH-LOGICAL-c453t-1bb953a8a90f6daa51a38883c8a7d2ca8fd3cc11c1d3d0e83140fb51fbb916c3
ISICitedReferencesCount	92
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000464086800065&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0196-8904
IngestDate	Sun Sep 28 01:17:11 EDT 2025 Wed Aug 13 09:38:54 EDT 2025 Tue Nov 18 22:12:47 EST 2025 Sat Nov 29 07:20:38 EST 2025 Fri Feb 23 02:47:09 EST 2024
IsDoiOpenAccess	false
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Keywords	Double-diode model Collaborative swarm intelligence Parameter estimation Single-diode model Hybrid metaheuristic
Language	English
LinkModel	OpenURL
MergedId	FETCHMERGED-LOGICAL-c453t-1bb953a8a90f6daa51a38883c8a7d2ca8fd3cc11c1d3d0e83140fb51fbb916c3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ORCID	0000-0002-6029-7032
OpenAccessLink	http://hdl.handle.net/10400.6/7051
PQID	2213146547
PQPubID	2047472
PageCount	25
ParticipantIDs	proquest_miscellaneous_2220840478 proquest_journals_2213146547 crossref_primary_10_1016_j_enconman_2019_02_003 crossref_citationtrail_10_1016_j_enconman_2019_02_003 elsevier_sciencedirect_doi_10_1016_j_enconman_2019_02_003
PublicationCentury	2000
PublicationDate	2019-04-01
PublicationDateYYYYMMDD	2019-04-01
PublicationDate_xml	– month: 04 year: 2019 text: 2019-04-01 day: 01
PublicationDecade	2010
PublicationPlace	Oxford
PublicationPlace_xml	– name: Oxford
PublicationTitle	Energy conversion and management
PublicationYear	2019
Publisher	Elsevier Ltd Elsevier Science Ltd
Publisher_xml	– name: Elsevier Ltd – name: Elsevier Science Ltd
References	Xiong, Zhang, Shi, He (b0205) 2018; 174 Xiong, Zhang, Yuan, Shi, He, Yao (b0260) 2018; 176 Kennedy, Eberhart (b0320) 1995 Niu, Zhang, Li (b0350) 2014; 86 Lin, Cheng, Yeh, Chen, Wu (b0065) 2017; 144 Xu, Wang (b0095) 2017; 144 Chen, Xu, Mei, Ding, Li (b0120) 2018; 212 Derick, Rani, Rajesh, Farrag, Wang, Busawon (b0155) 2017; 157 Gao, Cui, Hu, Tahir, Xu (b0200) 2018; 171 Lim, Ye, Ye, Yang, Du (b0040) 2015; 62 Wolpert, Macready (b0265) 1997; 1 Toledo, Blanes, Galiano (b0110) 2018; 65 Chan, Phang (b0070) 1987; 34 Harish Kumar (b0195) 2018; 71 Yu, Liang, Qu, Cheng, Wang (b0190) 2018; 226 Clerc (b0315) 2006; hal-001227 Mughal, Ma, Xiao (b0235) 2017; 10 Niu, Zhang, Li (b0345) 2014; 39 Ram, Babu, Dragicevic, Rajasekar (b0060) 2017; 135 Abd-Alsabour (b0220) 2016 Solar S. Sharp solar modules. ND-R250A5 2014:1–2. Nunes, Pombo, Mariano, Calado, Felippe de Souza (b0020) 2018; 211 Hamid, Abounacer, Idali Oumhand, Feddaoui, Agliz (b0165) 2018 Seyedmahmoudian, Mekhilef, Rahmani, Yusof, Renani (b0300) 2013; 6 Xiong, Zhang, Yuan, Shi, He, Xiong (b0215) 2018; 8 Gao, Cui, Hu, Xu, Wang, Qu (b0080) 2018; 157 Gow, Manning (b0285) 1999; 146 Ma, Bi, Ting, Hao, Hao (b0075) 2016; 132 Laudani, Riganti Fulginei, Salvini (b0100) 2014; 103 [accessed August 19, 2018]. Yao, Liu, Lin (b0365) 1999; 3 Villalva, Gazoli, Filho (b0030) 2009; 24 Kler, Sharma, Banerjee, Rana, Kumar (b0130) 2017; 35 Ishaque, Salam, Taheri (b0035) 2011; 95 Ertenlice, Kalayci (b0310) 2018; 39 Ma, Shen, Yu, Yang, Fei, Zhou (b0305) 2018 Ciulla, Lo Brano, Di Dio, Cipriani (b0010) 2014; 32 Hachana, Hemsas, Tina, Ventura (b0225) 2013; 5 Wu, Chen, Long, Cheng, Lin, Chen (b0255) 2018; 232 Jordehi (b0125) 2016; 129 Gao, Cui, Hu, Xu, Yu (b0290) 2016; 127 Abd Elaziz, Oliva (b0185) 2018; 171 Chen, Yu, Du, Zhao, Liu (b0335) 2016; 99 Aydilek (b0245) 2018; 66 Beigi, Maroosi (b0240) 2018; 171 Di Piazza, Vitale (b0005) 2013 Chin, Salam, Ishaque (b0270) 2015; 154 Abbassi, Abbassi, Jemli, Chebbi (b0025) 2018; 90 Rezaee Jordehi (b0160) 2018; 159 Wang, Zhan, Zhou (b0360) 2015; 8 Tossa, Soro, Azoumah, Yamegueu (b0090) 2014; 110 Muangkote, Sunat, Chiewchanwattana, Kaiwinit (b0210) 2019; 134 Soon, Low, Ting (b0045) 2014 Bayraktar, Komurcu, Werner (b0330) 2010 Oliva, Ewees, El, Hassanien, Peréz Cisneros (b0145) 2017; 10 Petrone, Ramos-Paja, Spagnuolo (b0280) 2017 Yu, Chen, Wang, Wang (b0140) 2017; 145 Easwarakhanthan, Bottin, Bouhouch, Boutrit (b0085) 1986; 4 Chen, Wu, Lin, Wu, Cheng (b0015) 2016; 182 Abdul Hamid, Rahim, Selvaraj (b0230) 2016; 8 Jordehi (b0275) 2016; 61 Louzazni, Khouya, Amechnoue, Gandelli, Mussetta, Crăciunescu (b0170) 2018; 8 Jamadi, Merrikh-Bayat, Bigdeli (b0355) 2016; 7 Kang, Bae, Yeung, Chung (b0250) 2018; 66 Cardenas, Carrasco, Mancilla-David, Street, Cardenas (b0105) 2017; 64 Fathy, Rezk (b0135) 2017; 111 Gong, Cai (b0050) 2013; 94 Oliva, Abd El Aziz, Ella Hassanien (b0055) 2017; 200 Elbaset, Ali, Abd El Sattar (b0295) 2016; 138 Mirjalili, Lewis (b0325) 2016; 95 Valdivia-González, Zaldívar, Cuevas, Pérez-Cisneros, Fausto, González (b0150) 2017; 10 Kang, Yao, Jin, Yang, Duong, Kang (b0175) 2018; 11 Suganthan, Hansen, Liang, Deb, Chen, Auger (b0370) 2005 Zhang, Lin, Chen, Cheng (b0340) 2016; 2016 Yu, Liang, Qu, Chen, Wang (b0115) 2017; 150 Chen, Sun, Meng (b0180) 2018; 169 Chen (10.1016/j.enconman.2019.02.003_b0180) 2018; 169 Laudani (10.1016/j.enconman.2019.02.003_b0100) 2014; 103 Yu (10.1016/j.enconman.2019.02.003_b0140) 2017; 145 Gao (10.1016/j.enconman.2019.02.003_b0080) 2018; 157 Yu (10.1016/j.enconman.2019.02.003_b0115) 2017; 150 Tossa (10.1016/j.enconman.2019.02.003_b0090) 2014; 110 Kang (10.1016/j.enconman.2019.02.003_b0250) 2018; 66 Valdivia-González (10.1016/j.enconman.2019.02.003_b0150) 2017; 10 Zhang (10.1016/j.enconman.2019.02.003_b0340) 2016; 2016 Suganthan (10.1016/j.enconman.2019.02.003_b0370) 2005 Fathy (10.1016/j.enconman.2019.02.003_b0135) 2017; 111 Kang (10.1016/j.enconman.2019.02.003_b0175) 2018; 11 Xiong (10.1016/j.enconman.2019.02.003_b0260) 2018; 176 Niu (10.1016/j.enconman.2019.02.003_b0350) 2014; 86 Ciulla (10.1016/j.enconman.2019.02.003_b0010) 2014; 32 Chen (10.1016/j.enconman.2019.02.003_b0335) 2016; 99 10.1016/j.enconman.2019.02.003_b0375 Hachana (10.1016/j.enconman.2019.02.003_b0225) 2013; 5 Petrone (10.1016/j.enconman.2019.02.003_b0280) 2017 Ertenlice (10.1016/j.enconman.2019.02.003_b0310) 2018; 39 Niu (10.1016/j.enconman.2019.02.003_b0345) 2014; 39 Xu (10.1016/j.enconman.2019.02.003_b0095) 2017; 144 Villalva (10.1016/j.enconman.2019.02.003_b0030) 2009; 24 Rezaee Jordehi (10.1016/j.enconman.2019.02.003_b0160) 2018; 159 Jordehi (10.1016/j.enconman.2019.02.003_b0275) 2016; 61 Xiong (10.1016/j.enconman.2019.02.003_b0215) 2018; 8 Harish Kumar (10.1016/j.enconman.2019.02.003_b0195) 2018; 71 Gong (10.1016/j.enconman.2019.02.003_b0050) 2013; 94 Chen (10.1016/j.enconman.2019.02.003_b0015) 2016; 182 Ma (10.1016/j.enconman.2019.02.003_b0075) 2016; 132 Nunes (10.1016/j.enconman.2019.02.003_b0020) 2018; 211 Wu (10.1016/j.enconman.2019.02.003_b0255) 2018; 232 Di Piazza (10.1016/j.enconman.2019.02.003_b0005) 2013 Gao (10.1016/j.enconman.2019.02.003_b0200) 2018; 171 Derick (10.1016/j.enconman.2019.02.003_b0155) 2017; 157 Lim (10.1016/j.enconman.2019.02.003_b0040) 2015; 62 Hamid (10.1016/j.enconman.2019.02.003_b0165) 2018 Beigi (10.1016/j.enconman.2019.02.003_b0240) 2018; 171 Abdul Hamid (10.1016/j.enconman.2019.02.003_b0230) 2016; 8 Mirjalili (10.1016/j.enconman.2019.02.003_b0325) 2016; 95 Chin (10.1016/j.enconman.2019.02.003_b0270) 2015; 154 Lin (10.1016/j.enconman.2019.02.003_b0065) 2017; 144 Chan (10.1016/j.enconman.2019.02.003_b0070) 1987; 34 Gow (10.1016/j.enconman.2019.02.003_b0285) 1999; 146 Yao (10.1016/j.enconman.2019.02.003_b0365) 1999; 3 Oliva (10.1016/j.enconman.2019.02.003_b0145) 2017; 10 Aydilek (10.1016/j.enconman.2019.02.003_b0245) 2018; 66 Gao (10.1016/j.enconman.2019.02.003_b0290) 2016; 127 Oliva (10.1016/j.enconman.2019.02.003_b0055) 2017; 200 Ram (10.1016/j.enconman.2019.02.003_b0060) 2017; 135 Mughal (10.1016/j.enconman.2019.02.003_b0235) 2017; 10 Seyedmahmoudian (10.1016/j.enconman.2019.02.003_b0300) 2013; 6 Easwarakhanthan (10.1016/j.enconman.2019.02.003_b0085) 1986; 4 Bayraktar (10.1016/j.enconman.2019.02.003_b0330) 2010 Abd Elaziz (10.1016/j.enconman.2019.02.003_b0185) 2018; 171 Muangkote (10.1016/j.enconman.2019.02.003_b0210) 2019; 134 Wolpert (10.1016/j.enconman.2019.02.003_b0265) 1997; 1 Abbassi (10.1016/j.enconman.2019.02.003_b0025) 2018; 90 Elbaset (10.1016/j.enconman.2019.02.003_b0295) 2016; 138 Jamadi (10.1016/j.enconman.2019.02.003_b0355) 2016; 7 Cardenas (10.1016/j.enconman.2019.02.003_b0105) 2017; 64 Ma (10.1016/j.enconman.2019.02.003_b0305) 2018 Abd-Alsabour (10.1016/j.enconman.2019.02.003_b0220) 2016 Jordehi (10.1016/j.enconman.2019.02.003_b0125) 2016; 129 Clerc (10.1016/j.enconman.2019.02.003_b0315) 2006; hal-001227 Toledo (10.1016/j.enconman.2019.02.003_b0110) 2018; 65 Ishaque (10.1016/j.enconman.2019.02.003_b0035) 2011; 95 Yu (10.1016/j.enconman.2019.02.003_b0190) 2018; 226 Chen (10.1016/j.enconman.2019.02.003_b0120) 2018; 212 Soon (10.1016/j.enconman.2019.02.003_b0045) 2014 Xiong (10.1016/j.enconman.2019.02.003_b0205) 2018; 174 Louzazni (10.1016/j.enconman.2019.02.003_b0170) 2018; 8 Kler (10.1016/j.enconman.2019.02.003_b0130) 2017; 35 Kennedy (10.1016/j.enconman.2019.02.003_b0320) 1995 Wang (10.1016/j.enconman.2019.02.003_b0360) 2015; 8
References_xml	– volume: 10 start-page: 1 year: 2017 end-page: 19 ident: b0145 article-title: A chaotic improved artificial bee colony for parameter estimation of photovoltaic cells publication-title: Energies – volume: 171 start-page: 1822 year: 2018 end-page: 1842 ident: b0200 article-title: Performance comparison of exponential, Lambert W function and special trans function based single diode solar cell models publication-title: Energy Convers Manage – year: 2013 ident: b0005 article-title: Photovoltaic sources – modeling and emulation – volume: 182 start-page: 47 year: 2016 end-page: 57 ident: b0015 article-title: Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy publication-title: Appl Energy – volume: 39 start-page: 36 year: 2018 end-page: 52 ident: b0310 article-title: A survey of swarm intelligence for portfolio optimization: algorithms and applications publication-title: Swarm Evol Comput – volume: 64 start-page: 1468 year: 2017 end-page: 1476 ident: b0105 article-title: Experimental parameter extraction in the single-diode photovoltaic model via a reduced-space search publication-title: IEEE Trans Ind Electron – start-page: 1 year: 2018 end-page: 8 ident: b0165 article-title: Parameters identification of photovoltaic solar cells and module using the genetic algorithm with convex combination crossover publication-title: Int J Ambient Energy – volume: 39 start-page: 3837 year: 2014 end-page: 3854 ident: b0345 article-title: An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models publication-title: Int J Hydrogen Energy – volume: 8 start-page: 1 year: 2016 end-page: 21 ident: b0230 article-title: Solar cell parameters identification using hybrid Nelder-Mead and modified particle swarm optimization publication-title: J Renewable Sustainable Energy – start-page: 1 year: 2018 end-page: 23 ident: b0305 article-title: Multi-population techniques in nature inspired optimization algorithms: a comprehensive survey publication-title: Swarm Evol Comput – volume: 132 start-page: 606 year: 2016 end-page: 616 ident: b0075 article-title: Comparative performance on photovoltaic model parameter identification via bio-inspired algorithms publication-title: Sol Energy – volume: 127 start-page: 443 year: 2016 end-page: 460 ident: b0290 article-title: Lambert W-function based exact representation for double diode model of solar cells: comparison on fitness and parameter extraction publication-title: Energy Convers Manage – volume: 24 start-page: 1198 year: 2009 end-page: 1208 ident: b0030 article-title: Comprehensive approach to modeling and simulation of photovoltaic arrays publication-title: IEEE Trans Power Electron – volume: 157 start-page: 460 year: 2018 end-page: 479 ident: b0080 article-title: Parameter extraction of solar cell models using improved shuffled complex evolution algorithm publication-title: Energy Convers Manage – start-page: 1 year: 2010 end-page: 4 ident: b0330 article-title: Wind driven optimization (WDO): a novel nature-inspired optimization algorithm and its application to electromagnetics publication-title: IEEE Antennas Propag. Soc. Int. Symp. – volume: 11 start-page: 1 year: 2018 end-page: 31 ident: b0175 article-title: A novel improved cuckoo search algorithm for parameter estimation of photovoltaic (PV) models publication-title: Energies – volume: 232 start-page: 36 year: 2018 end-page: 53 ident: b0255 article-title: Parameter extraction of photovoltaic models from measured I-V characteristics curves using a hybrid trust-region reflective algorithm publication-title: Appl Energy – volume: 135 start-page: 463 year: 2017 end-page: 476 ident: b0060 article-title: A new hybrid bee pollinator flower pollination algorithm for solar PV parameter estimation publication-title: Energy Convers Manage – volume: 144 start-page: 594 year: 2017 end-page: 603 ident: b0065 article-title: Parameters extraction of solar cell models using a modified simplified swarm optimization algorithm publication-title: Sol Energy – volume: 7 start-page: 13 year: 2016 end-page: 25 ident: b0355 article-title: Very accurate parameter estimation of single- and double-diode solar cell models using a modified artificial bee colony algorithm publication-title: Int J Energy Environ Eng – volume: 211 start-page: 774 year: 2018 end-page: 791 ident: b0020 article-title: A new high performance method for determining the parameters of PV cells and modules based on guaranteed convergence particle swarm optimization publication-title: Appl Energy – start-page: 2496 year: 2014 end-page: 2501 ident: b0045 article-title: Multi-dimension diode photovoltaic (PV) model for different PV cell technologies publication-title: IEEE 23rd Int. Symp. Ind. Electron. – volume: 66 start-page: 232 year: 2018 end-page: 249 ident: b0245 article-title: A hybrid firefly and particle swarm optimization algorithm for computationally expensive numerical problems publication-title: Appl Soft Comput – volume: 226 start-page: 408 year: 2018 end-page: 422 ident: b0190 article-title: Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models publication-title: Appl Energy – volume: 138 start-page: 26 year: 2016 end-page: 35 ident: b0295 article-title: New seven parameters model for amorphous silicon and thin film PV modules based on solar irradiance publication-title: Sol Energy – volume: 10 start-page: 1 year: 2017 end-page: 14 ident: b0235 article-title: Photovoltaic cell parameter estimation using hybrid particle swarm optimization and simulated annealing publication-title: Energies – volume: 103 start-page: 316 year: 2014 end-page: 326 ident: b0100 article-title: High performing extraction procedure for the one-diode model of a photovoltaic panel from experimental I-V curves by using reduced forms publication-title: Sol Energy – volume: 200 start-page: 141 year: 2017 end-page: 154 ident: b0055 article-title: Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm publication-title: Appl Energy – volume: 35 start-page: 93 year: 2017 end-page: 110 ident: b0130 article-title: PV cell and module efficient parameters estimation using evaporation rate based water cycle algorithm publication-title: Swarm Evol Comput – volume: 32 start-page: 684 year: 2014 end-page: 696 ident: b0010 article-title: A comparison of different one-diode models for the representation of I-V characteristic of a PV cell publication-title: Renewable Sustainable Energy Rev – volume: 10 start-page: 1 year: 2017 end-page: 25 ident: b0150 article-title: A chaos-embedded gravitational search algorithm for the identification of electrical parameters of photovoltaic cells publication-title: Energies – volume: 110 start-page: 543 year: 2014 end-page: 560 ident: b0090 article-title: A new approach to estimate the performance and energy productivity of photovoltaic modules in real operating conditions publication-title: Sol Energy – volume: 66 start-page: 319 year: 2018 end-page: 329 ident: b0250 article-title: A hybrid gravitational search algorithm with swarm intelligence and deep convolutional feature for object tracking optimization publication-title: Appl Soft Comput – volume: 8 start-page: 1 year: 2018 end-page: 18 ident: b0215 article-title: Application of symbiotic organisms search algorithm for parameter extraction of solar cell models publication-title: Appl Sci – volume: 146 start-page: 193 year: 1999 end-page: 200 ident: b0285 article-title: Development of a photovoltaic array model for use in power-electronics simulation studies publication-title: IEE Proc – Electr Power Appl – volume: 71 start-page: 141 year: 2018 end-page: 151 ident: b0195 article-title: Modeling of solar cell under different conditions by ant lion optimizer with LambertW function publication-title: Appl Soft Comput – volume: 99 start-page: 170 year: 2016 end-page: 180 ident: b0335 article-title: Parameters identification of solar cell models using generalized oppositional teaching learning based optimization publication-title: Energy – volume: 150 start-page: 742 year: 2017 end-page: 753 ident: b0115 article-title: Parameters identification of photovoltaic models using an improved JAYA optimization algorithm publication-title: Energy Convers Manage – volume: 61 start-page: 354 year: 2016 end-page: 371 ident: b0275 article-title: Parameter estimation of solar photovoltaic (PV) cells: a review publication-title: Renewable Sustainable Energy Rev – volume: 111 start-page: 307 year: 2017 end-page: 320 ident: b0135 article-title: Parameter estimation of photovoltaic system using imperialist competitive algorithm publication-title: Renewable Energy – volume: 90 start-page: 453 year: 2018 end-page: 474 ident: b0025 article-title: Identification of unknown parameters of solar cell models: a comprehensive overview of available approaches publication-title: Renewable Sustainable Energy Rev – volume: 95 start-page: 586 year: 2011 end-page: 594 ident: b0035 article-title: Simple, fast and accurate two-diode model for photovoltaic modules publication-title: Sol Energy Mater Sol Cells – volume: 5 start-page: 1 year: 2013 end-page: 18 ident: b0225 article-title: Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module publication-title: J Renewable Sustainable Energy – volume: 65 start-page: 6301 year: 2018 end-page: 6308 ident: b0110 article-title: Two-step linear least-squares method for photovoltaic single-diode model parameters extraction publication-title: IEEE Trans Ind Electron – volume: 3 start-page: 82 year: 1999 end-page: 102 ident: b0365 article-title: Evolutionary programming made faster publication-title: IEEE Trans Evol Comput – volume: 134 start-page: 1129 year: 2019 end-page: 1147 ident: b0210 article-title: An advanced onlooker-ranking-based adaptive differential evolution to extract the parameters of solar cell models publication-title: Renewable Energy – volume: 154 start-page: 500 year: 2015 end-page: 519 ident: b0270 article-title: Cell modelling and model parameters estimation techniques for photovoltaic simulator application: a review publication-title: Appl Energy – volume: 6 start-page: 128 year: 2013 end-page: 144 ident: b0300 article-title: Analytical modeling of partially shaded photovoltaic systems publication-title: Energies – volume: 4 start-page: 1 year: 1986 end-page: 12 ident: b0085 article-title: Nonlinear minimization algorithm for determining the solar cell parameters with microcomputers publication-title: Int J Sol Energy – volume: 157 start-page: 116 year: 2017 end-page: 124 ident: b0155 article-title: An improved optimization technique for estimation of solar photovoltaic parameters publication-title: Sol Energy – reference: [accessed August 19, 2018]. – volume: 2016 start-page: 1 year: 2016 end-page: 16 ident: b0340 article-title: A Population classification evolution algorithm for the parameter extraction of solar cell models publication-title: Int J Photoenergy – volume: 169 start-page: 345 year: 2018 end-page: 358 ident: b0180 article-title: An improved explicit double-diode model of solar cells: fitness verification and parameter extraction publication-title: Energy Convers Manage – volume: 129 start-page: 262 year: 2016 end-page: 274 ident: b0125 article-title: Time varying acceleration coefficients particle swarm optimisation (TVACPSO): a new optimisation algorithm for estimating parameters of PV cells and modules publication-title: Energy Convers Manage – volume: 171 start-page: 435 year: 2018 end-page: 446 ident: b0240 article-title: Parameter identification for solar cells and module using a hybrid firefly and pattern search algorithms publication-title: Sol Energy – volume: 34 start-page: 286 year: 1987 end-page: 293 ident: b0070 article-title: Analytical methods for the extraction of solar-cell single- and double-diode model parameters from I-V characteristics publication-title: IEEE Trans Electron Devices – volume: 171 start-page: 1843 year: 2018 end-page: 1859 ident: b0185 article-title: Parameter estimation of solar cells diode models by an improved opposition-based whale optimization algorithm publication-title: Energy Convers Manage – year: 2017 ident: b0280 publication-title: Photovoltaic sources modeling – start-page: 1942 year: 1995 end-page: 1948 ident: b0320 article-title: Particle swarm optimization publication-title: IEEE Int Conf Neural Networks – volume: 145 start-page: 233 year: 2017 end-page: 246 ident: b0140 article-title: Parameters identification of photovoltaic models using self-adaptive teaching-learning-based optimization publication-title: Energy Convers Manage – volume: 212 start-page: 1578 year: 2018 end-page: 1588 ident: b0120 article-title: Teaching–learning–based artificial bee colony for solar photovoltaic parameter estimation publication-title: Appl Energy – volume: 159 start-page: 78 year: 2018 end-page: 87 ident: b0160 article-title: Enhanced leader particle swarm optimisation (ELPSO): an efficient algorithm for parameter estimation of photovoltaic (PV) cells and modules publication-title: Sol Energy – volume: 174 start-page: 388 year: 2018 end-page: 405 ident: b0205 article-title: Parameter extraction of solar photovoltaic models using an improved whale optimization algorithm publication-title: Energy Convers Manage – volume: 95 start-page: 51 year: 2016 end-page: 67 ident: b0325 article-title: The whale optimization algorithm publication-title: Adv Eng Software – volume: 86 start-page: 1173 year: 2014 end-page: 1185 ident: b0350 article-title: A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells publication-title: Energy Convers Manage – volume: 8 start-page: 1 year: 2018 end-page: 22 ident: b0170 article-title: Metaheuristic algorithm for photovoltaic parameters: comparative study and prediction with a firefly algorithm publication-title: Appl Sci – reference: Solar S. Sharp solar modules. ND-R250A5 2014:1–2. – volume: hal-001227 start-page: 1 year: 2006 end-page: 9 ident: b0315 article-title: Confinements and biases in particle swarm optimisation publication-title: Sci Non Linéaire – start-page: 19 year: 2016 end-page: 33 ident: b0220 publication-title: Hybrid metaheuristics for classification problems – volume: 94 start-page: 209 year: 2013 end-page: 220 ident: b0050 article-title: Parameter extraction of solar cell models using repaired adaptive differential evolution publication-title: Sol Energy – volume: 176 start-page: 742 year: 2018 end-page: 761 ident: b0260 article-title: Parameter extraction of solar photovoltaic models by means of a hybrid differential evolution with whale optimization algorithm publication-title: Sol Energy – start-page: 2005005 year: 2005 ident: b0370 article-title: Special session on real-parameter optimization publication-title: KanGAL Rep – volume: 144 start-page: 53 year: 2017 end-page: 68 ident: b0095 article-title: Parameter estimation of photovoltaic modules using a hybrid flower pollination algorithm publication-title: Energy Convers Manage – volume: 1 start-page: 67 year: 1997 end-page: 82 ident: b0265 article-title: No free lunch theorems for optimization publication-title: IEEE Trans Evol Comput – volume: 62 start-page: 4181 year: 2015 end-page: 4193 ident: b0040 article-title: A linear identification of diode models from single I-V characteristics of PV panels publication-title: IEEE Trans Ind Electron – volume: 8 start-page: 7563 year: 2015 end-page: 7581 ident: b0360 article-title: Application of artificial bee colony in model parameter identification of solar cells publication-title: Energies – volume: 129 start-page: 262 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0125 article-title: Time varying acceleration coefficients particle swarm optimisation (TVACPSO): a new optimisation algorithm for estimating parameters of PV cells and modules publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2016.09.085 – volume: 174 start-page: 388 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0205 article-title: Parameter extraction of solar photovoltaic models using an improved whale optimization algorithm publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2018.08.053 – year: 2013 ident: 10.1016/j.enconman.2019.02.003_b0005 – volume: 145 start-page: 233 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0140 article-title: Parameters identification of photovoltaic models using self-adaptive teaching-learning-based optimization publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2017.04.054 – volume: 34 start-page: 286 year: 1987 ident: 10.1016/j.enconman.2019.02.003_b0070 article-title: Analytical methods for the extraction of solar-cell single- and double-diode model parameters from I-V characteristics publication-title: IEEE Trans Electron Devices doi: 10.1109/T-ED.1987.22920 – volume: 138 start-page: 26 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0295 article-title: New seven parameters model for amorphous silicon and thin film PV modules based on solar irradiance publication-title: Sol Energy doi: 10.1016/j.solener.2016.08.056 – volume: 212 start-page: 1578 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0120 article-title: Teaching–learning–based artificial bee colony for solar photovoltaic parameter estimation publication-title: Appl Energy doi: 10.1016/j.apenergy.2017.12.115 – volume: 135 start-page: 463 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0060 article-title: A new hybrid bee pollinator flower pollination algorithm for solar PV parameter estimation publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2016.12.082 – volume: 35 start-page: 93 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0130 article-title: PV cell and module efficient parameters estimation using evaporation rate based water cycle algorithm publication-title: Swarm Evol Comput doi: 10.1016/j.swevo.2017.02.005 – ident: 10.1016/j.enconman.2019.02.003_b0375 – volume: 226 start-page: 408 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0190 article-title: Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models publication-title: Appl Energy doi: 10.1016/j.apenergy.2018.06.010 – volume: 127 start-page: 443 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0290 article-title: Lambert W-function based exact representation for double diode model of solar cells: comparison on fitness and parameter extraction publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2016.09.005 – volume: 171 start-page: 1843 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0185 article-title: Parameter estimation of solar cells diode models by an improved opposition-based whale optimization algorithm publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2018.05.062 – volume: 103 start-page: 316 year: 2014 ident: 10.1016/j.enconman.2019.02.003_b0100 article-title: High performing extraction procedure for the one-diode model of a photovoltaic panel from experimental I-V curves by using reduced forms publication-title: Sol Energy doi: 10.1016/j.solener.2014.02.014 – volume: 159 start-page: 78 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0160 article-title: Enhanced leader particle swarm optimisation (ELPSO): an efficient algorithm for parameter estimation of photovoltaic (PV) cells and modules publication-title: Sol Energy doi: 10.1016/j.solener.2017.10.063 – start-page: 1 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0305 article-title: Multi-population techniques in nature inspired optimization algorithms: a comprehensive survey publication-title: Swarm Evol Comput – volume: 111 start-page: 307 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0135 article-title: Parameter estimation of photovoltaic system using imperialist competitive algorithm publication-title: Renewable Energy doi: 10.1016/j.renene.2017.04.014 – volume: 39 start-page: 36 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0310 article-title: A survey of swarm intelligence for portfolio optimization: algorithms and applications publication-title: Swarm Evol Comput doi: 10.1016/j.swevo.2018.01.009 – start-page: 1 year: 2010 ident: 10.1016/j.enconman.2019.02.003_b0330 article-title: Wind driven optimization (WDO): a novel nature-inspired optimization algorithm and its application to electromagnetics – volume: 7 start-page: 13 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0355 article-title: Very accurate parameter estimation of single- and double-diode solar cell models using a modified artificial bee colony algorithm publication-title: Int J Energy Environ Eng doi: 10.1007/s40095-015-0198-5 – volume: 95 start-page: 586 year: 2011 ident: 10.1016/j.enconman.2019.02.003_b0035 article-title: Simple, fast and accurate two-diode model for photovoltaic modules publication-title: Sol Energy Mater Sol Cells doi: 10.1016/j.solmat.2010.09.023 – volume: 146 start-page: 193 year: 1999 ident: 10.1016/j.enconman.2019.02.003_b0285 article-title: Development of a photovoltaic array model for use in power-electronics simulation studies publication-title: IEE Proc – Electr Power Appl doi: 10.1049/ip-epa:19990116 – volume: 99 start-page: 170 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0335 article-title: Parameters identification of solar cell models using generalized oppositional teaching learning based optimization publication-title: Energy doi: 10.1016/j.energy.2016.01.052 – volume: 3 start-page: 82 year: 1999 ident: 10.1016/j.enconman.2019.02.003_b0365 article-title: Evolutionary programming made faster publication-title: IEEE Trans Evol Comput doi: 10.1109/4235.771163 – volume: 10 start-page: 1 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0145 article-title: A chaotic improved artificial bee colony for parameter estimation of photovoltaic cells publication-title: Energies doi: 10.3390/en10070865 – volume: 8 start-page: 7563 year: 2015 ident: 10.1016/j.enconman.2019.02.003_b0360 article-title: Application of artificial bee colony in model parameter identification of solar cells publication-title: Energies doi: 10.3390/en8087563 – volume: 134 start-page: 1129 year: 2019 ident: 10.1016/j.enconman.2019.02.003_b0210 article-title: An advanced onlooker-ranking-based adaptive differential evolution to extract the parameters of solar cell models publication-title: Renewable Energy doi: 10.1016/j.renene.2018.09.017 – start-page: 2005005 year: 2005 ident: 10.1016/j.enconman.2019.02.003_b0370 article-title: Special session on real-parameter optimization publication-title: KanGAL Rep – volume: 144 start-page: 53 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0095 article-title: Parameter estimation of photovoltaic modules using a hybrid flower pollination algorithm publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2017.04.042 – volume: 10 start-page: 1 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0235 article-title: Photovoltaic cell parameter estimation using hybrid particle swarm optimization and simulated annealing publication-title: Energies doi: 10.3390/en10081213 – volume: 144 start-page: 594 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0065 article-title: Parameters extraction of solar cell models using a modified simplified swarm optimization algorithm publication-title: Sol Energy doi: 10.1016/j.solener.2017.01.064 – volume: 169 start-page: 345 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0180 article-title: An improved explicit double-diode model of solar cells: fitness verification and parameter extraction publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2018.05.035 – volume: 39 start-page: 3837 year: 2014 ident: 10.1016/j.enconman.2019.02.003_b0345 article-title: An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models publication-title: Int J Hydrogen Energy doi: 10.1016/j.ijhydene.2013.12.110 – start-page: 2496 year: 2014 ident: 10.1016/j.enconman.2019.02.003_b0045 article-title: Multi-dimension diode photovoltaic (PV) model for different PV cell technologies – volume: 8 start-page: 1 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0170 article-title: Metaheuristic algorithm for photovoltaic parameters: comparative study and prediction with a firefly algorithm publication-title: Appl Sci doi: 10.3390/app8030339 – volume: 154 start-page: 500 year: 2015 ident: 10.1016/j.enconman.2019.02.003_b0270 article-title: Cell modelling and model parameters estimation techniques for photovoltaic simulator application: a review publication-title: Appl Energy doi: 10.1016/j.apenergy.2015.05.035 – volume: 132 start-page: 606 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0075 article-title: Comparative performance on photovoltaic model parameter identification via bio-inspired algorithms publication-title: Sol Energy doi: 10.1016/j.solener.2016.03.033 – volume: 95 start-page: 51 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0325 article-title: The whale optimization algorithm publication-title: Adv Eng Software doi: 10.1016/j.advengsoft.2016.01.008 – volume: 157 start-page: 116 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0155 article-title: An improved optimization technique for estimation of solar photovoltaic parameters publication-title: Sol Energy doi: 10.1016/j.solener.2017.08.006 – volume: 150 start-page: 742 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0115 article-title: Parameters identification of photovoltaic models using an improved JAYA optimization algorithm publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2017.08.063 – volume: 232 start-page: 36 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0255 article-title: Parameter extraction of photovoltaic models from measured I-V characteristics curves using a hybrid trust-region reflective algorithm publication-title: Appl Energy doi: 10.1016/j.apenergy.2018.09.161 – volume: 11 start-page: 1 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0175 article-title: A novel improved cuckoo search algorithm for parameter estimation of photovoltaic (PV) models publication-title: Energies doi: 10.3390/en11051060 – volume: 5 start-page: 1 year: 2013 ident: 10.1016/j.enconman.2019.02.003_b0225 article-title: Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module publication-title: J Renewable Sustainable Energy doi: 10.1063/1.4822054 – volume: 65 start-page: 6301 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0110 article-title: Two-step linear least-squares method for photovoltaic single-diode model parameters extraction publication-title: IEEE Trans Ind Electron doi: 10.1109/TIE.2018.2793216 – volume: 1 start-page: 67 year: 1997 ident: 10.1016/j.enconman.2019.02.003_b0265 article-title: No free lunch theorems for optimization publication-title: IEEE Trans Evol Comput doi: 10.1109/4235.585893 – start-page: 1942 year: 1995 ident: 10.1016/j.enconman.2019.02.003_b0320 article-title: Particle swarm optimization publication-title: IEEE Int Conf Neural Networks – start-page: 1 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0165 article-title: Parameters identification of photovoltaic solar cells and module using the genetic algorithm with convex combination crossover publication-title: Int J Ambient Energy – volume: 157 start-page: 460 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0080 article-title: Parameter extraction of solar cell models using improved shuffled complex evolution algorithm publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2017.12.033 – volume: 24 start-page: 1198 year: 2009 ident: 10.1016/j.enconman.2019.02.003_b0030 article-title: Comprehensive approach to modeling and simulation of photovoltaic arrays publication-title: IEEE Trans Power Electron doi: 10.1109/TPEL.2009.2013862 – volume: 8 start-page: 1 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0230 article-title: Solar cell parameters identification using hybrid Nelder-Mead and modified particle swarm optimization publication-title: J Renewable Sustainable Energy – volume: 90 start-page: 453 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0025 article-title: Identification of unknown parameters of solar cell models: a comprehensive overview of available approaches publication-title: Renewable Sustainable Energy Rev doi: 10.1016/j.rser.2018.03.011 – volume: 66 start-page: 319 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0250 article-title: A hybrid gravitational search algorithm with swarm intelligence and deep convolutional feature for object tracking optimization publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2018.02.037 – start-page: 19 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0220 – volume: 71 start-page: 141 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0195 article-title: Modeling of solar cell under different conditions by ant lion optimizer with LambertW function publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2018.06.025 – volume: 61 start-page: 354 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0275 article-title: Parameter estimation of solar photovoltaic (PV) cells: a review publication-title: Renewable Sustainable Energy Rev doi: 10.1016/j.rser.2016.03.049 – volume: 110 start-page: 543 year: 2014 ident: 10.1016/j.enconman.2019.02.003_b0090 article-title: A new approach to estimate the performance and energy productivity of photovoltaic modules in real operating conditions publication-title: Sol Energy doi: 10.1016/j.solener.2014.09.043 – volume: 171 start-page: 1822 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0200 article-title: Performance comparison of exponential, Lambert W function and special trans function based single diode solar cell models publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2018.06.106 – year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0280 – volume: hal-001227 start-page: 1 year: 2006 ident: 10.1016/j.enconman.2019.02.003_b0315 article-title: Confinements and biases in particle swarm optimisation publication-title: Sci Non Linéaire – volume: 66 start-page: 232 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0245 article-title: A hybrid firefly and particle swarm optimization algorithm for computationally expensive numerical problems publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2018.02.025 – volume: 176 start-page: 742 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0260 article-title: Parameter extraction of solar photovoltaic models by means of a hybrid differential evolution with whale optimization algorithm publication-title: Sol Energy doi: 10.1016/j.solener.2018.10.050 – volume: 32 start-page: 684 year: 2014 ident: 10.1016/j.enconman.2019.02.003_b0010 article-title: A comparison of different one-diode models for the representation of I-V characteristic of a PV cell publication-title: Renewable Sustainable Energy Rev doi: 10.1016/j.rser.2014.01.027 – volume: 86 start-page: 1173 year: 2014 ident: 10.1016/j.enconman.2019.02.003_b0350 article-title: A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2014.06.026 – volume: 171 start-page: 435 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0240 article-title: Parameter identification for solar cells and module using a hybrid firefly and pattern search algorithms publication-title: Sol Energy doi: 10.1016/j.solener.2018.06.092 – volume: 182 start-page: 47 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0015 article-title: Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy publication-title: Appl Energy doi: 10.1016/j.apenergy.2016.08.083 – volume: 211 start-page: 774 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0020 article-title: A new high performance method for determining the parameters of PV cells and modules based on guaranteed convergence particle swarm optimization publication-title: Appl Energy doi: 10.1016/j.apenergy.2017.11.078 – volume: 6 start-page: 128 year: 2013 ident: 10.1016/j.enconman.2019.02.003_b0300 article-title: Analytical modeling of partially shaded photovoltaic systems publication-title: Energies doi: 10.3390/en6010128 – volume: 8 start-page: 1 year: 2018 ident: 10.1016/j.enconman.2019.02.003_b0215 article-title: Application of symbiotic organisms search algorithm for parameter extraction of solar cell models publication-title: Appl Sci doi: 10.3390/app8112155 – volume: 2016 start-page: 1 year: 2016 ident: 10.1016/j.enconman.2019.02.003_b0340 article-title: A Population classification evolution algorithm for the parameter extraction of solar cell models publication-title: Int J Photoenergy – volume: 200 start-page: 141 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0055 article-title: Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm publication-title: Appl Energy doi: 10.1016/j.apenergy.2017.05.029 – volume: 94 start-page: 209 year: 2013 ident: 10.1016/j.enconman.2019.02.003_b0050 article-title: Parameter extraction of solar cell models using repaired adaptive differential evolution publication-title: Sol Energy doi: 10.1016/j.solener.2013.05.007 – volume: 62 start-page: 4181 year: 2015 ident: 10.1016/j.enconman.2019.02.003_b0040 article-title: A linear identification of diode models from single I-V characteristics of PV panels publication-title: IEEE Trans Ind Electron doi: 10.1109/TIE.2015.2390193 – volume: 4 start-page: 1 year: 1986 ident: 10.1016/j.enconman.2019.02.003_b0085 article-title: Nonlinear minimization algorithm for determining the solar cell parameters with microcomputers publication-title: Int J Sol Energy doi: 10.1080/01425918608909835 – volume: 64 start-page: 1468 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0105 article-title: Experimental parameter extraction in the single-diode photovoltaic model via a reduced-space search publication-title: IEEE Trans Ind Electron doi: 10.1109/TIE.2016.2615590 – volume: 10 start-page: 1 year: 2017 ident: 10.1016/j.enconman.2019.02.003_b0150 article-title: A chaos-embedded gravitational search algorithm for the identification of electrical parameters of photovoltaic cells publication-title: Energies doi: 10.3390/en10071052
SSID	ssj0003506
Score	2.5690105
Snippet	•Collaborative swarm intelligence is proposed to estimate PV parameters.•The proposed methodology mitigates premature convergence and population... To properly evaluate, control and optimize photovoltaic (PV) systems, it is crucial to accurately estimate the equivalent electric circuit parameters from the...
SourceID	proquest crossref elsevier
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	866
SubjectTerms	case studies Circuits Collaborative swarm intelligence Computer applications Data processing Double-diode model electronic circuits Hybrid metaheuristic Intelligence Mathematical models Methodology Optimization Parameter estimation Photovoltaic cells Photovoltaics shade Shading Single-diode model Solar cells Stagnation Swarm intelligence system optimization
Title	Collaborative swarm intelligence to estimate PV parameters
URI	https://dx.doi.org/10.1016/j.enconman.2019.02.003 https://www.proquest.com/docview/2213146547 https://www.proquest.com/docview/2220840478
Volume	185
WOSCitedRecordID	wos000464086800065&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1879-2227 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0003506 issn: 0196-8904 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwELdg4wEeEJ-iMFCQEC9VRhw3sc1bmTrGVJVKhKlvluMkEhNNStOO_fmcP_JRBgweeImqtHYa3_l8Pt_9fgi94moUqXhU-JlkgT-SNPZTqbgPvrFG-5Y0yAxk_pTOZmyx4HMX060NnQAtS3Z5yVf_VdRwD4StS2f_Qdxtp3ADPoPQ4Qpih-tfCf6ok-xFPqy_y_XSgEK0wJvgbWpoDXBV8-H8bKjBv5c6KabeidLbmkCTlG4iauaUYXklWWa2dVj_J-87lq5qmdoDnXF70PMO2lS2uqRL9IV9ujTU38NPp47q2gUgMO_lrZioWFMZ0xijLh3JBCx57DNuKYYPc2tkGeW-rsHdtcJRz44yS8Vyxb7bUMP5oQb5LOGddW4et6CrpFvRmlP82Udx_Hk6FclkkbxeffM115g-k3fEKzfRfkgjDrZwf_xhsjhtV3ASGU7W9r_3Kst__ejfOTU_Le_GZ0nuobtus-GNrZLcRzfy8gG604OgfIje7qiLZ9TF66uLt6m8Rl28-ZnXqcsjlBxPkqMT3_Fp-DAhycbHacojIpnkQRFnUkZYEsYYUUzSLFSSFRlRCmOFM5IFOSOw-S7SCBfQDseKPEZ7ZVXmT5DHA5KNCpzygELXBZYxNlXZOeVRkCk6QFEzHkI5rHlNefJVNEmF56IZR6HHUQShRqkdoDdtu5VFW7m2BW-GWzif0fqCAlTm2rYHjXyEm8C1CEMM760puQfoZfs12Fx9kCbLvNrq34QBG2lcq6d_7uIZut3NmAO0t1lv8-folrrYfKnXL5za_QAjiqJ_
linkProvider	Elsevier
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Collaborative+swarm+intelligence+to+estimate+PV+parameters&rft.jtitle=Energy+conversion+and+management&rft.au=Nunes%2C+HGG&rft.au=Pombo%2C+JAN&rft.au=Bento%2C+PMR&rft.au=Mariano%2C+SJPS&rft.date=2019-04-01&rft.pub=Elsevier+Science+Ltd&rft.issn=0196-8904&rft.eissn=1879-2227&rft.volume=185&rft.spage=866&rft_id=info:doi/10.1016%2Fj.enconman.2019.02.003&rft.externalDBID=NO_FULL_TEXT
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0196-8904&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0196-8904&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0196-8904&client=summon