Evaluation of Reduced-Switch Seven-Level Converter-Based upqc with Hybrid Fuzzy-Feedforward Neural Network Algorithm
Abstract To improve the performance of end-user equipment in an electric utility distribution network, it is necessary to improve power quality (PQ). This paper presents PQ improvement in electric distribution network using seven-level five switch converter based Unified Power Quality Conditioner (7...
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Instituto de Tecnologia do Paraná (Tecpar)
2025-08-01
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| Series: | Brazilian Archives of Biology and Technology |
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| author | Veera Nagi Reddy Varampati Venkata Reddy Kota Ashok Kumar Devarasetty Venkata |
| author_facet | Veera Nagi Reddy Varampati Venkata Reddy Kota Ashok Kumar Devarasetty Venkata |
| author_sort | Veera Nagi Reddy Varampati |
| collection | DOAJ |
| description | Abstract To improve the performance of end-user equipment in an electric utility distribution network, it is necessary to improve power quality (PQ). This paper presents PQ improvement in electric distribution network using seven-level five switch converter based Unified Power Quality Conditioner (7LFSC-UPQC). Nowadays, power quality plays a vital role in the power distribution sector in the use of highly non-linear loads. Industrial non-linear loads produce electrical imbalances, thereby causing various voltage and current quality related problems, large amounts of harmonics, voltage swell, voltage sag, voltage interruption, etc. This paper proposes the design of a 7LFSC -UPQC based fuzzy-multilayer feed forward multi-layer neural network (FFMLNN) controller to mitigate PQ issues such as voltage sags, swells and current harmonics. A multi-layer feed forward neural network, in which a back-propagation algorithm is used to generate the appropriate reference voltage and current signals, and a shunt compensator of a seven-level unified power quality conditioner (UPQC). This proposed control scheme also controls the DC-link voltage and terminal voltage using an intelligent fuzzy controller. The performance of the proposed FFMLN-fuzzy based 7LFSC-UPQC configuration for simultaneous voltage swell, sag and total harmonic distortion is demonstrated and a comparative analysis of 7LFSC-UPQC and five level UPQC with PI-controller, fuzzy-controller and FFMLNN-controller is conducted using MATLAB/SIMULINK software. |
| format | Article |
| id | doaj-art-9b72d3004c07416fbb61378707522d92 |
| institution | Kabale University |
| issn | 1678-4324 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Instituto de Tecnologia do Paraná (Tecpar) |
| record_format | Article |
| series | Brazilian Archives of Biology and Technology |
| spelling | doaj-art-9b72d3004c07416fbb61378707522d922025-08-20T03:41:20ZengInstituto de Tecnologia do Paraná (Tecpar)Brazilian Archives of Biology and Technology1678-43242025-08-016810.1590/1678-4324-2025240682Evaluation of Reduced-Switch Seven-Level Converter-Based upqc with Hybrid Fuzzy-Feedforward Neural Network AlgorithmVeera Nagi Reddy Varampatihttps://orcid.org/0000-0001-8110-8029Venkata Reddy Kotahttps://orcid.org/0000-0003-3374-8018Ashok Kumar Devarasetty Venkatahttps://orcid.org/0000-0002-7317-4402Abstract To improve the performance of end-user equipment in an electric utility distribution network, it is necessary to improve power quality (PQ). This paper presents PQ improvement in electric distribution network using seven-level five switch converter based Unified Power Quality Conditioner (7LFSC-UPQC). Nowadays, power quality plays a vital role in the power distribution sector in the use of highly non-linear loads. Industrial non-linear loads produce electrical imbalances, thereby causing various voltage and current quality related problems, large amounts of harmonics, voltage swell, voltage sag, voltage interruption, etc. This paper proposes the design of a 7LFSC -UPQC based fuzzy-multilayer feed forward multi-layer neural network (FFMLNN) controller to mitigate PQ issues such as voltage sags, swells and current harmonics. A multi-layer feed forward neural network, in which a back-propagation algorithm is used to generate the appropriate reference voltage and current signals, and a shunt compensator of a seven-level unified power quality conditioner (UPQC). This proposed control scheme also controls the DC-link voltage and terminal voltage using an intelligent fuzzy controller. The performance of the proposed FFMLN-fuzzy based 7LFSC-UPQC configuration for simultaneous voltage swell, sag and total harmonic distortion is demonstrated and a comparative analysis of 7LFSC-UPQC and five level UPQC with PI-controller, fuzzy-controller and FFMLNN-controller is conducted using MATLAB/SIMULINK software.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132025000100611&tlng=enThree phase seven-level five switch UPQCFeed forward multi-layer neural networkFuzzy logicThree phase five level converterPower QualityBack Propagation algorithm. |
| spellingShingle | Veera Nagi Reddy Varampati Venkata Reddy Kota Ashok Kumar Devarasetty Venkata Evaluation of Reduced-Switch Seven-Level Converter-Based upqc with Hybrid Fuzzy-Feedforward Neural Network Algorithm Brazilian Archives of Biology and Technology Three phase seven-level five switch UPQC Feed forward multi-layer neural network Fuzzy logic Three phase five level converter Power Quality Back Propagation algorithm. |
| title | Evaluation of Reduced-Switch Seven-Level Converter-Based upqc with Hybrid Fuzzy-Feedforward Neural Network Algorithm |
| title_full | Evaluation of Reduced-Switch Seven-Level Converter-Based upqc with Hybrid Fuzzy-Feedforward Neural Network Algorithm |
| title_fullStr | Evaluation of Reduced-Switch Seven-Level Converter-Based upqc with Hybrid Fuzzy-Feedforward Neural Network Algorithm |
| title_full_unstemmed | Evaluation of Reduced-Switch Seven-Level Converter-Based upqc with Hybrid Fuzzy-Feedforward Neural Network Algorithm |
| title_short | Evaluation of Reduced-Switch Seven-Level Converter-Based upqc with Hybrid Fuzzy-Feedforward Neural Network Algorithm |
| title_sort | evaluation of reduced switch seven level converter based upqc with hybrid fuzzy feedforward neural network algorithm |
| topic | Three phase seven-level five switch UPQC Feed forward multi-layer neural network Fuzzy logic Three phase five level converter Power Quality Back Propagation algorithm. |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132025000100611&tlng=en |
| work_keys_str_mv | AT veeranagireddyvarampati evaluationofreducedswitchsevenlevelconverterbasedupqcwithhybridfuzzyfeedforwardneuralnetworkalgorithm AT venkatareddykota evaluationofreducedswitchsevenlevelconverterbasedupqcwithhybridfuzzyfeedforwardneuralnetworkalgorithm AT ashokkumardevarasettyvenkata evaluationofreducedswitchsevenlevelconverterbasedupqcwithhybridfuzzyfeedforwardneuralnetworkalgorithm |