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dc.contributor.authorSuppakarn Chansareewittayaen_US
dc.contributor.authorPeerapol Jirapongen_US
dc.date.accessioned2018-09-04T04:44:27Z-
dc.date.available2018-09-04T04:44:27Z-
dc.date.issued2010-12-01en_US
dc.identifier.other2-s2.0-79951649024en_US
dc.identifier.other10.1109/TENCON.2010.5685893en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79951649024&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/50697-
dc.description.abstractIn this paper, particle swarm optimization (PSO) is proposed to determine the optimal allocation of multitype FACTS controllers to enhance power transfer capability of power transactions between source and sink areas in power systems. The particularly optimal allocation includes optimal types, locations, and parameter settings. Three types of FACTS controllers including unified power flow controller (UPFC), thyristor-controlled series capacitor (TCSC), and static var compensator (SVC) are used in this study. The objective function is formulated as maximizing the benefit to cost ratio. The benefits mean increasing total transfer capability (TTC) with deducting system losses while the cost are the investment of FACTS controllers installation. Power transfer capability determinations are calculated based on optimal power flow (OPF) technique. Test results on the modified IEEE 30-bus system from PSO are compared with those from evolutionary programming (EP). The results show that PSO can be used to determine the optimal allocation of multitype FACTS controllers. The optimally placed OPF with FACTS controllers using PSO enhance higher power transfer capability than those from EP. Moreover, PSO gives higher benefit to cost ratio and faster convergence than EP for all transfer areas. Therefore, this installation is worthwhile and beneficial for the decision making of investment costs and further expansion plans. ©2010 IEEE.en_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titlePower transfer capability enhancement with multitype FACTS controllers using particle swarm optimizationen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleIEEE Region 10 Annual International Conference, Proceedings/TENCONen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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