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MMC-based PV-Fed STATCOM with Hybrid GA-RBFNN for PQ Enhancement.

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Title: MMC-based PV-Fed STATCOM with Hybrid GA-RBFNN for PQ Enhancement.
Authors: Umadevi, C.1 (AUTHOR) cumadevi.eee@gmail.com, Gnana Sundari, M.1 (AUTHOR) gnanasundari@gcetly.ac.in, Karuvelam, P. Subha1 (AUTHOR) subha@gcetly.ac.in
Source: IETE Journal of Research. Mar2024, Vol. 70 Issue 3, p3204-3221. 18p.
Subjects: Synchronous capacitors, DC-to-DC converters, Radial distribution function, Photovoltaic power systems, Political succession, Scalability
Abstract: Power quality (PQ) is a consequential factor, which is highly influenced by the functioning of the transmission and distribution network. In the distribution systems, voltage swells, sags, harmonics and flickers are regarded as major power quality issues. The Static Synchronous Compensator (STATCOM) is one among the specialized power devices, which has gained considerable interest for its capacity of enhancing the performance of power systems. This paper analyses the power quality issues of a photovoltaic (PV) system adopting a STATCOM-based five-level Modular Multilevel Converter (MMC). An interleaved quadratic boost converter (QBC) is employed in this work, which escalates the PV output in a wider range. An Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is employed for obtaining the fast, efficient and flexible control of the DC-DC converter. The MMC plays a crucial part in mitigating power quality issues as it has the beneficial impacts such as scalability, power quality and modularity. In this approach, a five-level MMC is implemented, which transfers active power to the load by maintaining the power factor constant. The reference current generation of MMC is carried out by a hybrid Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFNN) algorithm and the pulses of MMC are generated through a hysteresis controller. It provides improved training speed and convergence along with enhanced operating efficiency of the network. The output of five-level MMC is fed to a transformer-coupled LC filter. The simulations are carried out in Matlab and a minimized Total Harmonic Distortion (THD) of 1.12% is obtained. [ABSTRACT FROM AUTHOR]
Copyright of IETE Journal of Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: MMC-based PV-Fed STATCOM with Hybrid GA-RBFNN for PQ Enhancement.
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  Data: <searchLink fieldCode="AR" term="%22Umadevi%2C+C%2E%22">Umadevi, C.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> cumadevi.eee@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Gnana+Sundari%2C+M%2E%22">Gnana Sundari, M.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> gnanasundari@gcetly.ac.in</i><br /><searchLink fieldCode="AR" term="%22Karuvelam%2C+P%2E+Subha%22">Karuvelam, P. Subha</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> subha@gcetly.ac.in</i>
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  Data: <searchLink fieldCode="JN" term="%22IETE+Journal+of+Research%22">IETE Journal of Research</searchLink>. Mar2024, Vol. 70 Issue 3, p3204-3221. 18p.
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  Data: <searchLink fieldCode="DE" term="%22Synchronous+capacitors%22">Synchronous capacitors</searchLink><br /><searchLink fieldCode="DE" term="%22DC-to-DC+converters%22">DC-to-DC converters</searchLink><br /><searchLink fieldCode="DE" term="%22Radial+distribution+function%22">Radial distribution function</searchLink><br /><searchLink fieldCode="DE" term="%22Photovoltaic+power+systems%22">Photovoltaic power systems</searchLink><br /><searchLink fieldCode="DE" term="%22Political+succession%22">Political succession</searchLink><br /><searchLink fieldCode="DE" term="%22Scalability%22">Scalability</searchLink>
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  Label: Abstract
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  Data: Power quality (PQ) is a consequential factor, which is highly influenced by the functioning of the transmission and distribution network. In the distribution systems, voltage swells, sags, harmonics and flickers are regarded as major power quality issues. The Static Synchronous Compensator (STATCOM) is one among the specialized power devices, which has gained considerable interest for its capacity of enhancing the performance of power systems. This paper analyses the power quality issues of a photovoltaic (PV) system adopting a STATCOM-based five-level Modular Multilevel Converter (MMC). An interleaved quadratic boost converter (QBC) is employed in this work, which escalates the PV output in a wider range. An Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is employed for obtaining the fast, efficient and flexible control of the DC-DC converter. The MMC plays a crucial part in mitigating power quality issues as it has the beneficial impacts such as scalability, power quality and modularity. In this approach, a five-level MMC is implemented, which transfers active power to the load by maintaining the power factor constant. The reference current generation of MMC is carried out by a hybrid Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFNN) algorithm and the pulses of MMC are generated through a hysteresis controller. It provides improved training speed and convergence along with enhanced operating efficiency of the network. The output of five-level MMC is fed to a transformer-coupled LC filter. The simulations are carried out in Matlab and a minimized Total Harmonic Distortion (THD) of 1.12% is obtained. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IETE Journal of Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/03772063.2023.2192427
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        Text: English
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        PageCount: 18
        StartPage: 3204
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      – SubjectFull: Synchronous capacitors
        Type: general
      – SubjectFull: DC-to-DC converters
        Type: general
      – SubjectFull: Radial distribution function
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      – SubjectFull: Photovoltaic power systems
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      – SubjectFull: Political succession
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      – SubjectFull: Scalability
        Type: general
    Titles:
      – TitleFull: MMC-based PV-Fed STATCOM with Hybrid GA-RBFNN for PQ Enhancement.
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            NameFull: Gnana Sundari, M.
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            – D: 01
              M: 03
              Text: Mar2024
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              Y: 2024
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