Genetic algorithm type 2 fuzzy logic controller of microgrid system with a fractional-order technique

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dc.authorscopusidİlhami Çolak / 6602990030
dc.authorwosidİlhami Çolak / KVO-7460-2024
dc.contributor.authorMaroua, Bouziane
dc.contributor.authorLaid, Zarour
dc.contributor.authorBenbouhenni, Habib
dc.contributor.authorElbarbary Z.M.S.
dc.contributor.authorÇolak, İlhami
dc.contributor.authorAlammer, Mohammed M.
dc.date.accessioned2025-04-17T07:11:12Z
dc.date.available2025-04-17T07:11:12Z
dc.date.issued2025
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü
dc.description.abstractThis paper presents a hybrid approach that combines a genetic algorithm (GA)-optimized type-2 fuzzy logic controller (T2FLC) with a fractional-order technique for enhanced control of a microgrid system. The T2FLC approach is employed to handle the inherent uncertainties in the microgrid due to fluctuating renewable energy inputs and varying loads. The GA optimizes the parameters of the designed FO-T2FLC approach, ensuring optimal performance under different operational conditions. This developed strategy is a modification and development of the traditional approach, as it is characterized by rapid dynamic response, high durability, distinctive performance, ease of application, and inexpensive. Also, this designed strategy does not depend on the mathematical model of the studied system, which gives satisfactory results if the system parameters change. The microgrid system on the direct current side features a photovoltaic array with battery storage. In contrast, the alternating current section comprises a multi-functional voltage source inverter integrated with a shunt active power filter. This setup delivers energy to the connected loads and the network. To manage the system effectively; traditional power control methods (direct power control and space vector modulation) are used for the alternating current section. Additionally, the proposed regulator control the direct current bus voltage loop, regulate the reactive and active power loops of the network, and compensate for the total harmonic distortion in the source streams. It also injects the required active power into the network to enhance the competence of the power network. In this work, the efficiency of the proposed FO-T2FLC-GA approach is verified using MATLAB, comparing it to the T2FLC-GA approach and some existing strategies such as third-order sliding mode control. The results obtained highlight the effectiveness and strength of the FO-T2FLC-GA approach in improving power quality and reducing the total harmonic distortion value, as it reduces the total harmonic distortion value of the current by percentages estimated at 80%, 33.87%, and 32.50% in all cases. The FO-T2FLC-GA approach also reduces the steady-state error, undershoot, fluctuations, and overshoot of direct current link voltage compared to the T2FLC-GA approach by percentages estimated at 1.54%, 33.04%, 25%, and 33.04%, respectively. Compared with other works, the proposed approach improves the response time, overshoot, and ripples of direct current link voltage by 59.38%, 50%, and 75%, respectively, compared to the third-order sliding mode control approach. These results could make the designed FO-T2FLC-GA approach a prominent solution in the future in other industrial applications such as propulsion and traction.
dc.description.sponsorshipKing Khalid University
dc.identifier.citationMaroua, B., Laid, Z., Benbouhenni, H., Elbarbary, Z. M. S., Colak, I., & Alammer, M. M. (2025). Genetic algorithm type 2 fuzzy logic controller of microgrid system with a fractional-order technique. Scientific Reports, 15(1), 6318.
dc.identifier.doi10.1038/s41598-025-90239-1
dc.identifier.endpage30
dc.identifier.issn2045-2322
dc.identifier.issue1
dc.identifier.pmid39984545
dc.identifier.scopus2-s2.0-85218687649
dc.identifier.scopusqualityQ1
dc.identifier.startpage1
dc.identifier.urihttp://dx.doi.org/10.1038/s41598-025-90239-1
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6109
dc.identifier.volume15
dc.identifier.wosWOS:001428333900001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorÇolak, İlhami
dc.institutionauthoridİlhami Çolak / 0000-0002-6405-5938
dc.language.isoen
dc.publisherNature research
dc.relation.ispartofScientific reports
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBattery Storage
dc.subjectDirect Power Control
dc.subjectFractional-Order Technique
dc.subjectGenetic Algorithm
dc.subjectRenewable Energy
dc.subjectType-2 Fuzzy Logic Controller
dc.titleGenetic algorithm type 2 fuzzy logic controller of microgrid system with a fractional-order technique
dc.typeArticle

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