Publication:
A robust parameter estimation approach based on stochastic fractal search optimization algorithm applied to solar PV parameters

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dc.citedby38
dc.contributor.authorRezk H.en_US
dc.contributor.authorBabu T.S.en_US
dc.contributor.authorAl-Dhaifallah M.en_US
dc.contributor.authorZiedan H.A.en_US
dc.contributor.authorid55425573200en_US
dc.contributor.authorid56267551500en_US
dc.contributor.authorid57217855650en_US
dc.contributor.authorid16687187300en_US
dc.date.accessioned2023-05-29T09:05:40Z
dc.date.available2023-05-29T09:05:40Z
dc.date.issued2021
dc.descriptionDiodes; Equivalent circuits; Fractals; Optimization; Parameter estimation; Photovoltaic cells; Stochastic systems; Equivalent circuit model; Optimization algorithms; Performance parameters; Renewable energies; Robust parameter estimation; Search optimization; Single-diode models; Solar photovoltaics; Solar cellsen_US
dc.description.abstractModeling of solar photovoltaic (PV) cell/modules to estimate its parameters with the measured current�voltage (I�V ) values is a very important issue for the control, optimization, and effectiveness of the PV systems. Therefore, in this research work, a robust approach based on Stochastic Fractal Search (SFS) optimization algorithm is introduced to estimate accurate and reliable values of solar PV parameters for its precise modeling. To assess the excellence of the proposed SFS algorithm, different solar PV equivalent circuit models, i.e. single-diode model (SDM), double-diode model (DDM), and PV module model are taken into consideration. The introduced algorithm is examined under three different case studies; (i) first case study: an experimental standard dataset of a commercial R.T.C. France silicon solar cell working at 33�C, and solar radiance of 1000 W/m2; (ii) second case study: using a polycrystalline solar panel STP6 120/36 with 36 cells in series working at 22�C, and (iii) third case study: an experimental dataset of ESP-160 PPW PV module working at 45�C, this experimentation were carried out in the Laboratory of Renewable Energy at Assiut University, Egypt. The results obtained using the proposed method are compared with other recently published works, and hence, the achieved results show the superiority, perfectness, and effective modeling concerning various performance parameters. Thereby, the proposed SFS approach can be used for effective PV modeling to improve the efficiency of the PV system. � 2021 The Authorsen_US
dc.description.natureFinalen_US
dc.identifier.doi10.1016/j.egyr.2021.01.024
dc.identifier.epage640
dc.identifier.scopus2-s2.0-85099617012
dc.identifier.spage620
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85099617012&doi=10.1016%2fj.egyr.2021.01.024&partnerID=40&md5=dedad4f510b92ce1bafab9650c025153
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25941
dc.identifier.volume7
dc.publisherElsevier Ltden_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleEnergy Reports
dc.titleA robust parameter estimation approach based on stochastic fractal search optimization algorithm applied to solar PV parametersen_US
dc.typeArticleen_US
dspace.entity.typePublication
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