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dc.contributor.authorBiswal, Saubhagya Ranjan
dc.contributor.authorShankar, Gauri
dc.contributor.authorElavarasan, Rajvikram Madurai
dc.contributor.authorMihet-Popa, Lucian
dc.identifier.citationIEEE Access. 2021, 9, 125658-125677.en_US
dc.description.abstractIncreased load demands worsen distribution system problems such as greater line losses, voltage deviation and a plethora of other concerns. This current work presents an approach stressing simultaneous optimal allocation and sizing of capacitor banks and distributed generations, as well as optimal radial distribution system (RDS) reconfiguration, to address these difficulties. The above objectives are accomplished through the maiden application of the proposed quasi-reflection-based slime mould algorithm (QRSMA). The efficacy of QRSMA is established by testing it on different benchmark functions. A new modified backward forward load flow approach is also proposed and validated by comparing its results to those obtained using MATPOWER software for IEEE 69, 85, and 118 bus RDSs. The proposed load flow technique is independent of the sequential bus numbering scheme and may be applied to any RDS network topology. The proposed QRSMA is tested on 118 bus RDS and to prove its effectiveness; its results are compared to those of other studied algorithms. The study takes into account both fixed and variable loading scenarios. A cost-benefit analysis of the strategy is also performed in order to make the methodology more realistic.en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.subjectcapacitor banksen_US
dc.subjectdistributed generationen_US
dc.subjectnetwork reconfigurationen_US
dc.subjectquasi-reflection-based slime mould algorithmen_US
dc.subjectradial distribution systemen_US
dc.titleOptimal Allocation/Sizing of DGs/Capacitors in Reconfigured Radial Distribution System using Quasi-Reflected Slime Mould Algorithmen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.subject.nsiVDP::Teknologi: 500en_US
dc.source.journalIEEE Accessen_US

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Navngivelse 4.0 Internasjonal
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