dc.contributorUniv Malaya
dc.contributorUniv Kuala Lumpur
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorNatl Cheng Kung Univ
dc.date.accessioned2018-11-26T17:45:06Z
dc.date.available2018-11-26T17:45:06Z
dc.date.created2018-11-26T17:45:06Z
dc.date.issued2018-02-27
dc.identifierIet Generation Transmission & Distribution. Hertford: Inst Engineering Technology-iet, v. 12, n. 4, p. 976-986, 2018.
dc.identifier1751-8687
dc.identifierhttp://hdl.handle.net/11449/163822
dc.identifier10.1049/iet-gtd.2017.1134
dc.identifierWOS:000424423500021
dc.identifierWOS000424423500021.pdf
dc.description.abstractReconfiguring the link between buses is a crucial task to enhance the distribution system performance. Reconfiguration is a complex combinatorial process due to numerous feasible solutions. Therefore, to consistently find global optimum solutions within a short span of time is a challenging task. One of the factors that cause time consumption in finding optimal network configurations is the elimination of non-radiality network solutions during the optimisation process. To address this issue, this work proposes to store pre-determined network radiality solutions in a database. These sets of solutions are used in the network reconfiguration optimisation by a discrete evolutionary programming and a discrete evolutionary particle swarm optimisation techniques. These optimisation methods are based on a multi-objective problem which minimises power loss, voltage deviation, and a number of switching actions. Moreover, the quality of the solutions is measured in terms of computational time and consistency. To demonstrate the efficiency of the proposed technique, a comparative assessment is carried out on 33-bus and 118-bus distribution systems. It is found that the proposed technique outperforms other existing methods in terms of quality of the solutions.
dc.languageeng
dc.publisherInst Engineering Technology-iet
dc.relationIet Generation Transmission & Distribution
dc.relation0,907
dc.rightsAcesso aberto
dc.sourceWeb of Science
dc.subjectevolutionary computation
dc.subjectparticle swarm optimisation
dc.subjectcombinatorial mathematics
dc.subjectdatabase management systems
dc.subjectmathematics computing
dc.subjectdistribution networks
dc.subjectpower engineering computing
dc.subjectintegrated database approach
dc.subjectmultiobjective network reconfiguration
dc.subjectdistribution system performance enhancement
dc.subjectcomplex combinatorial process
dc.subjectglobal optimum solutions
dc.subjectoptimal network configurations
dc.subjectnonradiality network solution elimination
dc.subject33-bus distribution systems
dc.subject118-bus distribution systems
dc.subjectswitching actions
dc.subjectvoltage deviation
dc.subjectpower loss minimization
dc.subjectdiscrete evolutionary particle swarm optimisation techniques
dc.subjectdiscrete evolutionary programming
dc.subjectnetwork reconfiguration optimisation
dc.subjectpre-determined network radiality solutions
dc.titleIntegrated database approach in multi-objective network reconfiguration for distribution system using discrete optimisation techniques
dc.typeArtículos de revistas


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