Power Quality Enhancement in Hybrid PV-BES System based on ANN-MPPT

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dc.contributor.authorBozkurt, Helin
dc.contributor.authorCelik, Ozgur
dc.contributor.authorTeke, Ahmet
dc.date.accessioned2025-03-17T12:25:10Z
dc.date.available2025-03-17T12:25:10Z
dc.date.issued2024
dc.departmentTarsus Üniversitesi
dc.description.abstractBattery energy systems (BESs) assisted photovoltaic (PV) plants are among the popular hybrid power systems in terms of energy efficiency, energy management, uninterrupted power supply, grid-connected and off-grid availability. The primary objective of this study is to enhance the power quality of a grid-tied PV-BES hybrid system by developing an operational strategy based on artificial neural network (ANN) based maximum power point tracking (MPPT) method. A test system comprising a 10-kWh BES and a 12.4 kW PV plant is structured and simulated on the MATLAB/Simulink platform. The hybrid system is validated with three different cases: constant radiation, rapid changing radiation, and real-day solar radiation data from the Turkish State Meteorological Service of Tarsus (Mersin, Turkiye) employing the developed operational strategy. These cases involve the examination of three distinct MPPT methods, analyzing DC-link voltage, battery state of charge (SOC), current, voltage, and system total harmonic distortion (THD). The simulation results indicate that the developed operational strategy with the ANN-MPPT method yields superior THD results in output current and a more stable DC-link voltage. Furthermore, the strategy shows improved convergence speed and reduced oscillations to achieve diverse reference operating points under varying atmospheric conditions compared to conventional MPPT methods. Numerical results demonstrate that the developed operational strategy with the ANN-MPPT consistently maintains THD values below 3% and exhibits a stable DC-link voltage deviation of 1.42% in various charging modes for both rapidly changing radiation and real-day solar radiation data.
dc.identifier.doi10.55730/1300-0632.4094
dc.identifier.issn1300-0632
dc.identifier.issn1303-6203
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85205150086
dc.identifier.scopusqualityQ2
dc.identifier.trdizinid1264632
dc.identifier.urihttps://doi.org/10.55730/1300-0632.4094
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1264632
dc.identifier.urihttps://hdl.handle.net/20.500.13099/1511
dc.identifier.volume32
dc.identifier.wosWOS:001321123900001
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.publisherTubitak Scientific & Technological Research Council Turkey
dc.relation.ispartofTurkish Journal of Electrical Engineering and Computer Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250316
dc.subjectBattery energy storage system (BESs)
dc.subjecttotal harmonic distortion (THD)
dc.subjectANN-based MPPT
dc.subjectgrid connected hybrid systems
dc.subjectpower quality enhancement
dc.titlePower Quality Enhancement in Hybrid PV-BES System based on ANN-MPPT
dc.typeArticle

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