Unified Power Flow Controller for PV Systems Using AI-Driven Power Quality Improvement Using Coupled Inductor Dual Boost Converter

Voltage stability, power flow regulation, and Power Quality have become major issues as a result of the increasing integration of renewable energy sources, especially photovoltaic (PV) systems, into power transmission networks. The main objective of this research is to improve the power quality (PQ)...

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Main Authors: Chindam A., IlanjiAkilandam C., DugyalaV.
Format: Article
Language:English
Published: Academy of Sciences of Moldova 2025-08-01
Series:Problems of the Regional Energetics
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Online Access:https://journal.ie.asm.md/assets/files/16_03_67_2025.pdf
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author Chindam A.
IlanjiAkilandam C.
DugyalaV.
author_facet Chindam A.
IlanjiAkilandam C.
DugyalaV.
author_sort Chindam A.
collection DOAJ
description Voltage stability, power flow regulation, and Power Quality have become major issues as a result of the increasing integration of renewable energy sources, especially photovoltaic (PV) systems, into power transmission networks. The main objective of this research is to improve the power quality (PQ) in power system utilizing Renewable Energy Sources (RESs), notably by eliminating the harmonic content in voltage and current that arise from power electronics interfaces. To address this, a Unified Power Flow Controller (UPFC), is proposed comprising both series and shunt converters interlinked with DC-link capacitor. In addition, a Photovoltaic (PV) system is integrated with a Coupled Inductor Dual Boost (CIDB) converter to ensure a stable and continuous energy supply. To accomplish these objectives, a Coyote Optimized Radial Basis Function Neural Network (COA-RBFNN) based Maximum Power Point Tracking (MPPT) is adopted for ensuring efficient energy extraction from PV system. Furthermore, a Decoupled Neural Network (DNN) based control technique is integrated to manage UPFC efficiently. The research is modelled and simulated in Matlab. The most important results of the study demonstrate a significant improvement in improving PQ, even under changing load conditions. Moreover, the converter ranks with improved efficiency of 88%, with improved voltage and current characteristics. The significance of the results is found in the ability to integrate renewable energy with contemporary power control technologies while guaranteeing dependable and high-quality power delivery.
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issn 1857-0070
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publisher Academy of Sciences of Moldova
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series Problems of the Regional Energetics
spelling doaj-art-27dffb4e4fc54218960d40860b3204d32025-08-20T02:47:47ZengAcademy of Sciences of MoldovaProblems of the Regional Energetics1857-00702025-08-01673187202310.52254/1857-0070.2025.3-67.16 Unified Power Flow Controller for PV Systems Using AI-Driven Power Quality Improvement Using Coupled Inductor Dual Boost ConverterChindam A.0IlanjiAkilandam C.1DugyalaV. 2Annamalai University, IndiaAnnamalai University, IndiaKamala Institute of Technology and Science, Telangana, India.Voltage stability, power flow regulation, and Power Quality have become major issues as a result of the increasing integration of renewable energy sources, especially photovoltaic (PV) systems, into power transmission networks. The main objective of this research is to improve the power quality (PQ) in power system utilizing Renewable Energy Sources (RESs), notably by eliminating the harmonic content in voltage and current that arise from power electronics interfaces. To address this, a Unified Power Flow Controller (UPFC), is proposed comprising both series and shunt converters interlinked with DC-link capacitor. In addition, a Photovoltaic (PV) system is integrated with a Coupled Inductor Dual Boost (CIDB) converter to ensure a stable and continuous energy supply. To accomplish these objectives, a Coyote Optimized Radial Basis Function Neural Network (COA-RBFNN) based Maximum Power Point Tracking (MPPT) is adopted for ensuring efficient energy extraction from PV system. Furthermore, a Decoupled Neural Network (DNN) based control technique is integrated to manage UPFC efficiently. The research is modelled and simulated in Matlab. The most important results of the study demonstrate a significant improvement in improving PQ, even under changing load conditions. Moreover, the converter ranks with improved efficiency of 88%, with improved voltage and current characteristics. The significance of the results is found in the ability to integrate renewable energy with contemporary power control technologies while guaranteeing dependable and high-quality power delivery. https://journal.ie.asm.md/assets/files/16_03_67_2025.pdfpower quality (pq)pvcoupled inductor dual boost convertercoyote optimized rbfnn mpptdnn.
spellingShingle Chindam A.
IlanjiAkilandam C.
DugyalaV.
Unified Power Flow Controller for PV Systems Using AI-Driven Power Quality Improvement Using Coupled Inductor Dual Boost Converter
Problems of the Regional Energetics
power quality (pq)
pv
coupled inductor dual boost converter
coyote optimized rbfnn mppt
dnn.
title Unified Power Flow Controller for PV Systems Using AI-Driven Power Quality Improvement Using Coupled Inductor Dual Boost Converter
title_full Unified Power Flow Controller for PV Systems Using AI-Driven Power Quality Improvement Using Coupled Inductor Dual Boost Converter
title_fullStr Unified Power Flow Controller for PV Systems Using AI-Driven Power Quality Improvement Using Coupled Inductor Dual Boost Converter
title_full_unstemmed Unified Power Flow Controller for PV Systems Using AI-Driven Power Quality Improvement Using Coupled Inductor Dual Boost Converter
title_short Unified Power Flow Controller for PV Systems Using AI-Driven Power Quality Improvement Using Coupled Inductor Dual Boost Converter
title_sort unified power flow controller for pv systems using ai driven power quality improvement using coupled inductor dual boost converter
topic power quality (pq)
pv
coupled inductor dual boost converter
coyote optimized rbfnn mppt
dnn.
url https://journal.ie.asm.md/assets/files/16_03_67_2025.pdf
work_keys_str_mv AT chindama unifiedpowerflowcontrollerforpvsystemsusingaidrivenpowerqualityimprovementusingcoupledinductordualboostconverter
AT ilanjiakilandamc unifiedpowerflowcontrollerforpvsystemsusingaidrivenpowerqualityimprovementusingcoupledinductordualboostconverter
AT dugyalav unifiedpowerflowcontrollerforpvsystemsusingaidrivenpowerqualityimprovementusingcoupledinductordualboostconverter