Optimal Placement and Sizing of Static Var Compensators in Radial Distribution Networks Using Artificial Intelligence Techniques

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dc.contributor.authorJafrouni, H.
dc.contributor.authorAlmaktar, M.
dc.contributor.authorMohamed, F.A.
dc.contributor.authorElbreki, A.M.
dc.contributor.authorRajab, Z.
dc.date.accessioned2024-09-29T16:21:01Z
dc.date.available2024-09-29T16:21:01Z
dc.date.issued2023
dc.departmentKarabük Üniversitesien_US
dc.descriptionOrange TM; STCen_US
dc.description15th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2023 -- 29 June 2023 through 30 June 2023 -- Bucharest -- 191300en_US
dc.description.abstractEnergy conservation and efficiency are necessary actions in electrical power system. Therefore, the wasted energy that is dissipated in the transmission network needs to be minimized. The power loss can be reduced by using many techniques, including the use of reactive compensators. In this paper, intelligent algorithms are examined to find the best site and size of reactive compensators so as to improve the performance, power quality and economics of radial electrical networks. A Matlab program has been developed to find the status of a radial distribution network in terms of power flow, losses, and bus voltages. Two artificial intelligence (AI) algorithms namely genetic algorithm (GA) and particle swarm optimization (PSO) have been developed to cater for the optimal position and amount of reactive power compensation. The programmed approaches were tested in reference network of IEEE 15-bus system and then implemented on the Syrian network, specifically Al-Mayadeen distribution network comprising 64-bus. Transient Electrolyzer Program (ETAP) was used to simulate the different power systems. The study showed that the GA is superior and outperforms PSO in reducing total power loss hence the cost and also improving voltage profile. Overall, the two examined techniques can be used in any radial electrical network. © 2023 IEEE.en_US
dc.identifier.doi10.1109/ECAI58194.2023.10194155
dc.identifier.isbn979-835032138-8
dc.identifier.scopus2-s2.0-85168092639en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/ECAI58194.2023.10194155
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9470
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof15th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2023 - Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGenetic algorithmen_US
dc.subjectparticle swarm optimizationen_US
dc.subjectradial electrical networken_US
dc.subjectreactive power consumptionen_US
dc.titleOptimal Placement and Sizing of Static Var Compensators in Radial Distribution Networks Using Artificial Intelligence Techniquesen_US
dc.typeConference Objecten_US

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