Modified grasshopper optimization algorithm optimized adaptive fuzzy lead-lag controller for coordinated design of FACTS controller with PSS

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dc.authoridTofigh Allahviranloo / 0000-0002-3929-9762en_US
dc.authorscopusidTofigh Allahviranloo / 8834494700en_US
dc.authorwosidTofigh Allahviranloo / V-4843-2019en_US
dc.contributor.authorSahu, Preeti Ranjan
dc.contributor.authorHota, Prakash Kumar
dc.contributor.authorPanda, Sidhartha
dc.contributor.authorLong, Hoang Viet
dc.contributor.authorAllahviranloo, Tofigh
dc.date.accessioned2022-11-11T08:20:15Z
dc.date.available2022-11-11T08:20:15Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Matematik Bölümüen_US
dc.description.abstractThis paper proposes adaptive fuzzy lead-lag controller structures for power system stabilizer and flexible AC transmission system based damping controllers to increase the stability of power system. The parameters of the proposed controller are tuned by a modified grasshopper optimization algorithm (MGOA). The new algorithm named MGOA accomplishes a proper balance between exploration and exploitation phases of original grasshopper optimization algorithm. This capability of MGOA is certified by using the benchmark functions by comparing with that of a grasshopper optimization algorithm, genetic algorithm, evolutionary strategies, particle swarm optimization, bat algorithm, population based incremental learning, flower pollination algorithm, monarch butterfly optimization and improved monarch butterfly optimization. The proposed controller is optimized and verified under various loading circumstances using MGOA method. The results of MGOA are compared with grasshopper optimization algorithm, genetic algorithm, and particle swarm optimization. Additionally, the results of the proposed MGOA are compared with conventional lead-lag controller to demonstrate its superiority.en_US
dc.identifier.citationSahu, P. R., Hota, P. K., Panda, S., Long, H. V., & Allahviranloo, T. Modified grasshopper optimization algorithm optimized adaptive fuzzy lead-lag controller for coordinated design of FACTS controller with PSS. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-20.en_US
dc.identifier.doi10.3233/JIFS-212716en_US
dc.identifier.endpage5094en_US
dc.identifier.issue4en_US
dc.identifier.startpage5075en_US
dc.identifier.urihttps://doi.org/10.3233/JIFS-212716
dc.identifier.urihttps://hdl.handle.net/20.500.12713/3332
dc.identifier.volume43en_US
dc.identifier.wosWOS:000841691300081en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.institutionauthorAllahviranloo, Tofigh
dc.language.isoenen_US
dc.publisherIOS PRESSen_US
dc.relation.ispartofJOURNAL OF INTELLIGENT & FUZZY SYSTEMSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectModified Grasshopper Optimization Algorithmen_US
dc.subjectStatic Synchronous Series Compensatoren_US
dc.subjectAdaptive Fuzzy Lead-lag Controlleren_US
dc.subjectPower System Stabilityen_US
dc.titleModified grasshopper optimization algorithm optimized adaptive fuzzy lead-lag controller for coordinated design of FACTS controller with PSSen_US
dc.typeArticleen_US

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