Optimal PSS design using FDB-based social network search algorithm in multi-machine power systems

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dc.contributor.authorKaymaz, Enes
dc.contributor.authorGüvenç, Uğur
dc.contributor.authorDöşoğlu, Mehmet Kenan
dc.date.accessioned2023-07-26T11:55:17Z
dc.date.available2023-07-26T11:55:17Z
dc.date.issued2023
dc.departmentDÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractThe optimal design of Power System Stabilizer (PSS) parameters is a significant optimization problem in power systems. Metaheuristic search (MHS) algorithms are among the most commonly used methods for optimizing PSS parameters. The preferred MHS algorithm must have strong exploration capability and an effective exploitation-exploration balance. The Fitness-Distance Balance (FDB) is a novel method for MHS algorithms, and it is featured by balanced search and effective diversity capabilities. In this paper, the exploration and balanced search capabilities of the Social Network Search (SNS) have been developed by using the FDB method. The FDB method guides the search process in the SNS and enables a more efficient selection of solution candidates in the search space. The performance of FDB-based SNS (FDBSNS) has been tested in the CEC-2014 and CEC-2017 benchmark test suits, and its superiority against SNS has been verified. Moreover, the effect of the FDBSNS was investigated in WSCC 3-machine 9-bus and 10-machine 39-bus New England test systems in the optimal PSS design problem. The obtained results and statistical analyses demonstrated that FDBSNS is a robust MHS algorithm compared to the algorithms in the literature for solving the CEC benchmark suits and optimal PSS design problem.en_US
dc.identifier.doi10.1007/s00521-023-08356-9
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.scopus2-s2.0-85149382298en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-023-08356-9
dc.identifier.urihttps://hdl.handle.net/20.500.12684/13042
dc.identifier.wosWOS:000944095200001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorKaymaz, Enes; Güvenç, Uğur; Döşoğlu, Mehmet Kenan
dc.language.isoenen_US
dc.publisherSpringer London Ltden_US
dc.relation.ispartofNeural Computing & Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz$2023V1Guncelleme$en_US
dc.subjectFitness-Distance Balance (Fdb); Social Network Search (Sns) Algorithm; Power System Stabilizer (Pss); Metaheuristic Search (Mhs) Algorithmen_US
dc.subjectKnowledge-Based Algorithm; Stability Enhancement; Adaptive Parameters; Optimization; Intelligence; Testsen_US
dc.titleOptimal PSS design using FDB-based social network search algorithm in multi-machine power systemsen_US
dc.typeArticleen_US

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