Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/77666
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dc.contributor.authorChatuphat Karaaomen_US
dc.contributor.authorPeerapol Jirapongen_US
dc.contributor.authorPanida Thararaken_US
dc.date.accessioned2022-10-16T08:12:05Z-
dc.date.available2022-10-16T08:12:05Z-
dc.date.issued2020-10-14en_US
dc.identifier.other2-s2.0-85107294325en_US
dc.identifier.other10.1109/ICPEI49860.2020.9431479en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85107294325&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/77666-
dc.description.abstractRegarding the increase in electrical power demands, distributed generations (DGs) from renewable energy resources are becoming essential for electrical generation systems. However, there are no specific requirements for DGs allocation in a distribution network. The improper installation of the DGs can cause crucial issues to electric utilities and customers, such as the increase in energy losses and the improper voltage drop in the networks. In this paper, the optimal distribution network reconfiguration implemented with a tie line and a capacitor is proposed to enhance system efficiency and mitigate the impacts of the improper DGs installation. The optimal allocation of the tie line and the capacitor is determined using an improved particle swarm optimization (I-PSO) technique to minimize the energy losses and improve the voltage profile. The proposed network reconfiguration approach is implemented into a practical distribution network with a high installed capacity of the biomass DG unit from Kamphaeng Phet province, Thailand. The simulation test results show that the proposed approach can significantly reduce not only the energy losses but also the voltage drop in the network.en_US
dc.subjectEnergyen_US
dc.subjectEngineeringen_US
dc.subjectSocial Sciencesen_US
dc.titleOptimal Distribution Network Reconfiguration Implemented with Tie Line and Capacitor Using Improved Particle Swarm Optimizationen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleProceedings of the 2020 International Conference on Power, Energy and Innovations, ICPEI 2020en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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