Metaheuristic-based automatic generation controller in interconnected power systems with renewable energy sources

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dc.authorscopusid57720481500en_US
dc.authorscopusid36974966800en_US
dc.authorscopusid35103037800en_US
dc.contributor.authorCan, Ö.
dc.contributor.authorEroğlu, H.
dc.contributor.authorÖztürk, A.
dc.date.accessioned2024-08-23T16:07:39Z
dc.date.available2024-08-23T16:07:39Z
dc.date.issued2023en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractIt is necessary to minimize fluctuations in system frequency and tie-line power deviations to provide high-quality, reliable, and stable electrical power. Automatic Generation Control (AGC) is the essential control process to keep the frequency and tie-line power change between acceptable values in interconnected power systems. Problems such as stability, peak deviation, and transient response are the general disadvantages of studies in the literature. To eliminate these disadvantages and to improve parameters such as maximum/minimum overshoot, and settling time, we propose a novel controller named PID-(1+I) for AGC in a two-area nonreheat thermal power system integrated with renewable energy sources (RESs) such as photovoltaic (PV) panels and wind turbines (WTs). The gain parameters of the proposed controller are optimally tuned by newly developed metaheuristic algorithms such as Gorilla Troops Optimizer (GTO), African Vulture Optimization Algorithm (AVOA), and Honey Badger Algorithm (HBA). To examine the effectiveness of the proposed controller, the system is tested under conditions such as random load change, RES generation, and system parameter change. The results show that the proposed controller gives remarkable results in terms of overshoot and settling time values. © 2023 Elsevier Inc. All rights reserved.en_US
dc.identifier.doi10.1016/B978-0-323-91781-0.00015-6
dc.identifier.endpage311en_US
dc.identifier.isbn978-032391781-0en_US
dc.identifier.isbn978-032397267-3en_US
dc.identifier.scopus2-s2.0-85158981068en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage293en_US
dc.identifier.urihttps://doi.org/10.1016/B978-0-323-91781-0.00015-6
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14765
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofComprehensive Metaheuristics: Algorithms and Applicationsen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAfrican vulture optimization algorithmen_US
dc.subjectAutomatic generation control (AGC)en_US
dc.subjectGorilla troops optimizeren_US
dc.subjectHoney badger algorithmen_US
dc.subjectMetaheuristic optimization techniquesen_US
dc.subjectNonreheat thermal power systemsen_US
dc.subjectPID-(1 + I) controlleren_US
dc.subjectRenewable energy sourcesen_US
dc.titleMetaheuristic-based automatic generation controller in interconnected power systems with renewable energy sourcesen_US
dc.typeBook Chapteren_US

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