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dc.contributor.authorArif, SMen_NZ
dc.contributor.authorHussain, Aen_NZ
dc.contributor.authorLie, TTen_NZ
dc.contributor.authorAhsan, SMen_NZ
dc.contributor.authorKhan, HAen_NZ
dc.date.accessioned2020-10-22T03:27:12Z
dc.date.available2020-10-22T03:27:12Z
dc.date.copyright2020-10-30en_NZ
dc.identifier.citationJournal of Modern Power Systems and Clean Energy, doi: 10.35833/MPCE.2019.000143
dc.identifier.issn2196-5420en_NZ
dc.identifier.urihttp://hdl.handle.net/10292/13732
dc.description.abstractIn this paper, the hybridization of standard particle swarm optimisation (PSO) with the analytical method (2/3rd rule) is proposed, which is called as analytical hybrid PSO (AHPSO) algorithm used for the optimal siting and sizing of distribution generation. The proposed AHPSO algorithm is implemented to cater for uniformly distributed, increasingly distributed, centrally distributed, and randomly distributed loads in conventional power systems. To demonstrate the effectiveness of the proposed algorithm, the convergence speed and optimization performances of standard PSO and the proposed AHPSO algorithms are compared for two cases. in the first case, the performances of both the algorithms are compared for four different load distributions via an IEEE 10-bus system. In the second case, the performances of both the algorithms are compared for IEEE 10-bus, IEEE 33-bus, IEEE 69-bus systems, and a real distribution system of Korea. Simulation results show that the proposed AHPSO algorithm converges significantly faster than the standard PSO. The results of the proposed algorithm are compared with those of an analytical algorithm, and the results of them are similar.
dc.publisherIEEEen_NZ
dc.relation.urihttps://ieeexplore.ieee.org/document/9205717
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
dc.subjectSiting and sizing of distributed generation; Distribution system; Hybrid algorithm; Loss minimization; Particle swarm optimization (PSO)
dc.titleAnalytical Hybrid Particle Swarm Optimization Algorithm for Optimal Siting and Sizing of Distributed Generation in Smart Griden_NZ
dc.typeJournal Article
dc.rights.accessrightsOpenAccessen_NZ
dc.identifier.doi10.35833/MPCE.2019.000143en_NZ
pubs.elements-id392876
aut.relation.journalJournal of Modern Power Systems and Clean Energyen_NZ


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