A Hybrid ANFIS-ABC Based MPPT Controller for PV System with Anti-Islanding Grid Protection: Experimental Realization

S. Padmanaban, N. Priyadarshi, M. S. Bhaskar, J. B. Holm-Nielsen, V. K. Ramachandaramurthy, E. Hossain

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Resumé

This paper introduces a novel control system with maximum power point tracker (MPPT) for the photovoltaic system with grid integration. Hybrid adaptive neuro-fuzzy inference system (ANFIS) and artificial bee colony (ABC) algorithm employed to optimize the membership function. Hence, for minimizing the root mean square error (RMSE), this controls the SEPIC-based MPPT algorithm to achieve rapid PV power tracking. The system performance is improved by fuzzy logic control (FLC), which generates the switching signal to the power switches of the inverter. A dSPACE (DS1104) control board employed for experimental validation of MPPT and inverter control strategies. The novelty of the proposed hybrid MPPT controller is the optimal tuning of ANFIS membership function with the ABC algorithm and been neither discussed before for PV power applications. The experimental responses completely validate the reliability of the PV grid integration with anti-islanding protection. The recentness of this research work is PV MPPT functioning using the hybrid ANFIS-ABC-based algorithm, been not described practically by any researchers in the past works.
OriginalsprogEngelsk
TidsskriftIEEE Access
Vol/bind7
Antal sider13
ISSN2169-3536
DOI
StatusUdgivet - jul. 2019

Fingerprint

Fuzzy inference
Controllers
Membership functions
Mean square error
Fuzzy logic
Tuning
Switches
Maximum power point trackers
Control systems

Emneord

  • Maximum power point trackers
  • Inverters
  • Fuzzy logic
  • Meteorology
  • Control systems
  • Artificial neural networks
  • Particle swarm optimization
  • ANFIS-ABC
  • dSPACE
  • Fuzzy Logic Controller
  • MPPT
  • Photovoltaic
  • SEPIC

Citer dette

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abstract = "This paper introduces a novel control system with maximum power point tracker (MPPT) for the photovoltaic system with grid integration. Hybrid adaptive neuro-fuzzy inference system (ANFIS) and artificial bee colony (ABC) algorithm employed to optimize the membership function. Hence, for minimizing the root mean square error (RMSE), this controls the SEPIC-based MPPT algorithm to achieve rapid PV power tracking. The system performance is improved by fuzzy logic control (FLC), which generates the switching signal to the power switches of the inverter. A dSPACE (DS1104) control board employed for experimental validation of MPPT and inverter control strategies. The novelty of the proposed hybrid MPPT controller is the optimal tuning of ANFIS membership function with the ABC algorithm and been neither discussed before for PV power applications. The experimental responses completely validate the reliability of the PV grid integration with anti-islanding protection. The recentness of this research work is PV MPPT functioning using the hybrid ANFIS-ABC-based algorithm, been not described practically by any researchers in the past works.",
keywords = "Maximum power point trackers, Inverters, Fuzzy logic, Meteorology, Control systems, Artificial neural networks, Particle swarm optimization, ANFIS-ABC, dSPACE, Fuzzy Logic Controller, MPPT, Photovoltaic, SEPIC, ANFIS-ABC, dSPACE, Fuzzy logic controller, MPPT, Photovoltaic, SEPIC",
author = "S. Padmanaban and N. Priyadarshi and Bhaskar, {M. S.} and Holm-Nielsen, {J. B.} and Ramachandaramurthy, {V. K.} and E. Hossain",
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A Hybrid ANFIS-ABC Based MPPT Controller for PV System with Anti-Islanding Grid Protection: Experimental Realization. / Padmanaban, S.; Priyadarshi, N.; Bhaskar, M. S.; Holm-Nielsen, J. B.; Ramachandaramurthy, V. K.; Hossain, E.

I: IEEE Access, Bind 7, 07.2019.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - A Hybrid ANFIS-ABC Based MPPT Controller for PV System with Anti-Islanding Grid Protection: Experimental Realization

AU - Padmanaban, S.

AU - Priyadarshi, N.

AU - Bhaskar, M. S.

AU - Holm-Nielsen, J. B.

AU - Ramachandaramurthy, V. K.

AU - Hossain, E.

PY - 2019/7

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N2 - This paper introduces a novel control system with maximum power point tracker (MPPT) for the photovoltaic system with grid integration. Hybrid adaptive neuro-fuzzy inference system (ANFIS) and artificial bee colony (ABC) algorithm employed to optimize the membership function. Hence, for minimizing the root mean square error (RMSE), this controls the SEPIC-based MPPT algorithm to achieve rapid PV power tracking. The system performance is improved by fuzzy logic control (FLC), which generates the switching signal to the power switches of the inverter. A dSPACE (DS1104) control board employed for experimental validation of MPPT and inverter control strategies. The novelty of the proposed hybrid MPPT controller is the optimal tuning of ANFIS membership function with the ABC algorithm and been neither discussed before for PV power applications. The experimental responses completely validate the reliability of the PV grid integration with anti-islanding protection. The recentness of this research work is PV MPPT functioning using the hybrid ANFIS-ABC-based algorithm, been not described practically by any researchers in the past works.

AB - This paper introduces a novel control system with maximum power point tracker (MPPT) for the photovoltaic system with grid integration. Hybrid adaptive neuro-fuzzy inference system (ANFIS) and artificial bee colony (ABC) algorithm employed to optimize the membership function. Hence, for minimizing the root mean square error (RMSE), this controls the SEPIC-based MPPT algorithm to achieve rapid PV power tracking. The system performance is improved by fuzzy logic control (FLC), which generates the switching signal to the power switches of the inverter. A dSPACE (DS1104) control board employed for experimental validation of MPPT and inverter control strategies. The novelty of the proposed hybrid MPPT controller is the optimal tuning of ANFIS membership function with the ABC algorithm and been neither discussed before for PV power applications. The experimental responses completely validate the reliability of the PV grid integration with anti-islanding protection. The recentness of this research work is PV MPPT functioning using the hybrid ANFIS-ABC-based algorithm, been not described practically by any researchers in the past works.

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