An effective method based on simulated annealing for automatic generation control of power systems

Basit Öğe Kaydı
dc.contributor.authorTabak, Abdulsamed
dc.contributor.authorIlhan, Ilhan
dc.date.accessioned2024-02-23T14:02:11Z
dc.date.available2024-02-23T14:02:11Z
dc.date.issued2022
dc.departmentNEÜen_US
dc.description.abstractIn this study, a novel hybrid Simulated Annealing-Genetic Algorithm (hSA-GA) is proposed. In the hSA-GA, population-based SA is used and each solution in the population is improved using the local search operator. The information exchange between the improved solutions is provided by the crossover operator. A new selection operator is used to ensure the balance between intensification and diversification. The hSA-GA is tested first on nine benchmark functions. Then it is used for tuning proportional-integral-derivative (PID) parameters for automatic generation control (AGC) of multi-area interconnected power systems. Firstly, PID parameters are determined with hSA-GA on a two-area interconnected non-reheating thermal system (System-1) in two different generator time constants. Secondly, to demonstrate the effect of supplementary control in AGC systems, the system is simulated with hSA-GA tuned PID controller and without controller. Additionally, the performance of the proposed hSA-GA is observed on AGC system of two area thermal power system with governor dead-band (GDB) nonlinearity (System-2). Transient responses of delta f(1), delta f(2) and delta P-tie obtained for both System-1 and System-2 are compared with studies on the same systems in the literature and it is seen that hSA-GA exhibits better control performance on power systems than compared studies. The proposed algorithm shows the best performance in System-1 (when T-g = 0.08). Accordingly, settling times of delta f(1), delta f(2) and delta P-tie are reduced to 2.33 s, 3.783 s and 3.11 s, respectively. Finally, the non-linear two area thermal power system is tested with a load varying between +/- 50% for 180 s to validation of proposed algorithm and results are compared relevant studies. (C) 2022 Elsevier B.V. All rights reserved.en_US
dc.identifier.doi10.1016/j.asoc.2022.109277
dc.identifier.issn1568-4946
dc.identifier.issn1872-9681
dc.identifier.scopus2-s2.0-85134562812en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.asoc.2022.109277
dc.identifier.urihttps://hdl.handle.net/20.500.12452/11621
dc.identifier.volume126en_US
dc.identifier.wosWOS:000863473800003en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofApplied Soft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHybrid Simulated Annealing-Genetic Algorithmen_US
dc.subjectMulti-Area Power Systemen_US
dc.subjectAutomatic Generation Controlen_US
dc.subjectPid Controlleren_US
dc.subjectGovernor Dead Banden_US
dc.subjectOptimizationen_US
dc.titleAn effective method based on simulated annealing for automatic generation control of power systemsen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu