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Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm

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dc.citedby66
dc.contributor.authorMuhsen D.H.en_US
dc.contributor.authorGhazali A.B.en_US
dc.contributor.authorKhatib T.en_US
dc.contributor.authorAbed I.A.en_US
dc.contributor.authorid56728928200en_US
dc.contributor.authorid56727852400en_US
dc.contributor.authorid31767521400en_US
dc.contributor.authorid55568292900en_US
dc.date.accessioned2023-05-29T05:59:59Z
dc.date.available2023-05-29T05:59:59Z
dc.date.issued2015
dc.descriptionAlgorithms; Evolutionary algorithms; Mean square error; Optimization; Parameter estimation; Photovoltaic cells; Coefficient of determination; DEAM; Five parameters; Hybrid differential evolution; Improved differential evolutions; IV characteristics; Photovoltaic modules; Root mean square errors; Iterative methods; algorithm; artificial intelligence; electromagnetic method; error analysis; experimental study; photovoltaic systemen_US
dc.description.abstractIn this paper, an improved differential evolution with adaptive mutation per iteration algorithm (DEAM) is proposed for extracting PV module's model parameters. DEAM utilizes the attraction-repulsion concept which is used in the electromagnetism to boost the mutation operation of the original differential evolution (DE). Furthermore, a new formula to adjust the mutation scaling factor and crossover rate for each generation is proposed. The proposed method has been validated by experimental data and other previous methods. The results of the proposed method show a high agreement between the experimental and simulated I- V characteristics. The average root mean square error, mean bias error, coefficient of determination and CPU-execution time of the proposed method are 1.744%, 0.158%, 99.21% and 18.5975. s respectively. According to the results, the proposed method offers better performance than other methods in terms of accuracy, CPU-execution time and convergence. � 2015 Elsevier Ltd.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1016/j.solener.2015.07.008
dc.identifier.epage297
dc.identifier.scopus2-s2.0-84937500751
dc.identifier.spage286
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84937500751&doi=10.1016%2fj.solener.2015.07.008&partnerID=40&md5=9340345745cb84b1993ae142bda37687
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22278
dc.identifier.volume119
dc.publisherElsevier Ltden_US
dc.sourceScopus
dc.sourcetitleSolar Energy
dc.titleExtraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
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