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Comparison of Various Control Strategies for UPQC to Mitigate PQ Issues
https://orcid.org/http://orcid.org/0000-0003-0987-5148
In this manuscript, numerous intelligent projected methods have been implemented to enhance UPQC device power quality (PQ) problems. The numerous intelligent methods are artificial neural network (ANN) controller, fuzzy logic controller (FLC), neuro-fuzzy controller (NFC) and adaptive neuro-fuzzy interference system (ANFIS). In addition, numerous optimization control methodologies are used to series active power filters and shunt active power filters. The intelligent control methods were implemented in the MATLAB/Simulink platform, and the efficacy of the anticipated technique is investigated via the comparison investigation with the conservative methods. The performance of adaptive ANFIS is used for enlightening the performance of PQ of the UPQC device. Lastly, the projected method of simulation is investigated and to mitigate the voltage sag/swell in UPQC device than the available approaches.
Comparison of Various Control Strategies for UPQC to Mitigate PQ Issues
https://orcid.org/http://orcid.org/0000-0003-0987-5148
In this manuscript, numerous intelligent projected methods have been implemented to enhance UPQC device power quality (PQ) problems. The numerous intelligent methods are artificial neural network (ANN) controller, fuzzy logic controller (FLC), neuro-fuzzy controller (NFC) and adaptive neuro-fuzzy interference system (ANFIS). In addition, numerous optimization control methodologies are used to series active power filters and shunt active power filters. The intelligent control methods were implemented in the MATLAB/Simulink platform, and the efficacy of the anticipated technique is investigated via the comparison investigation with the conservative methods. The performance of adaptive ANFIS is used for enlightening the performance of PQ of the UPQC device. Lastly, the projected method of simulation is investigated and to mitigate the voltage sag/swell in UPQC device than the available approaches.
Comparison of Various Control Strategies for UPQC to Mitigate PQ Issues
https://orcid.org/http://orcid.org/0000-0003-0987-5148
In this manuscript, numerous intelligent projected methods have been implemented to enhance UPQC device power quality (PQ) problems. The numerous intelligent methods are artificial neural network (ANN) controller, fuzzy logic controller (FLC), neuro-fuzzy controller (NFC) and adaptive neuro-fuzzy interference system (ANFIS). In addition, numerous optimization control methodologies are used to series active power filters and shunt active power filters. The intelligent control methods were implemented in the MATLAB/Simulink platform, and the efficacy of the anticipated technique is investigated via the comparison investigation with the conservative methods. The performance of adaptive ANFIS is used for enlightening the performance of PQ of the UPQC device. Lastly, the projected method of simulation is investigated and to mitigate the voltage sag/swell in UPQC device than the available approaches.
Comparison of Various Control Strategies for UPQC to Mitigate PQ Issues
J. Inst. Eng. India Ser. B
Rajendran, Manivasagam (author)
2021-02-01
11 pages
Article (Journal)
Electronic Resource
English
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