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dc.contributor.authorMohapatra, Bhabasis
dc.contributor.authorSahu, Binod Kumar
dc.contributor.authorPati, Swagat
dc.contributor.authorBajaj, Mohit
dc.contributor.authorBlažek, Vojtěch
dc.contributor.authorProkop, Lukáš
dc.contributor.authorMišák, Stanislav
dc.date.accessioned2024-11-20T13:28:03Z
dc.date.available2024-11-20T13:28:03Z
dc.date.issued2024
dc.identifier.citationScientific Reports. 2024, vol. 14, issue 1, art. no. 4646.cs
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/10084/155326
dc.description.abstractOver the past years, the use of renewable energy sources (RESs) has grown significantly as a means of providing clean energy to counteract the devastating effects of climate change. Reducing energy costs and pollution have been the primary causes of the rise in solar photovoltaic (PV) system integrations with the grid in recent years. A load that is locally connected to a GCPV requires both active and reactive power control. In order to control both active and reactive power, MAs and advanced controllers are essential. Researchers have used one of the recently developed MAs, known as the CAOA, which is based on mathematical arithmetic operators to tackle a few real-world optimization problems. Some disadvantages of CAOA include its natural tendency to converge to a local optimum and its limited capacity for exploration. By merging the PSO and CAOA methodologies, this article suggests the IAOA. To show how applicable IAOA is, its performance has been evaluated using four benchmark functions. The implementation of an IAOA-based ST-SMC for active and reactive power control is addressed in this article, which offers an innovative approach of research. In comparison to PSO-based ST-SMC and CAOA-based ST-SMC, the proposed IAOA-based ST-SMC appears to be superior, with settling time for active and reactive power control at a minimum of 0.01012 s and 0.5075 s. A real-time OPAL-RT 4510 simulator is used to validate the performance results of a 40 kW GCPV system after it has been investigated in the MATLAB environment.cs
dc.language.isoencs
dc.publisherSpringer Naturecs
dc.relation.ispartofseriesScientific Reportscs
dc.relation.urihttps://doi.org/10.1038/s41598-024-55380-3cs
dc.rightsCopyright © 2024, The Author(s)cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectimproved arithmetic optimization algorithm (IAOA)cs
dc.subjectparticle swarm optimization (PSO)cs
dc.subjectsuper twisting sliding mode controller (ST-SMC)cs
dc.subjectproportional-integral (PI) controllercs
dc.subjectconventional arithmetic optimization algorithm (CAOA)cs
dc.subjectgrid connected photovoltaic system (GCPV)cs
dc.subjectphotovoltaic (PV)cs
dc.titleOptimizing grid-connected PV systems with novel super-twisting sliding mode controllers for real-time power managementcs
dc.typearticlecs
dc.identifier.doi10.1038/s41598-024-55380-3
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume14cs
dc.description.issue1cs
dc.description.firstpageart. no. 4646cs
dc.identifier.wos001177429500095


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