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

doi:10.1109/ACCESS.2019.2931547

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

Research output: Contribution to journal › Journal article › Research › peer-review

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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.

Original language	English
Journal	IEEE Access
Volume	7
Number of pages	13
ISSN	2169-3536
DOIs	https://doi.org/10.1109/ACCESS.2019.2931547
Publication status	Published - Jul 2019

Keywords

ANFIS-ABC
dSPACE
Fuzzy logic controller
MPPT
Photovoltaic
SEPIC

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10.1109/ACCESS.2019.2931547

Open Access articleFinal published version, 13.1 MBLicence: CC BY 4.0

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@article{81abc0864f8f4d75a4826413e6995aab,

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

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",

year = "2019",

month = jul,

doi = "10.1109/ACCESS.2019.2931547",

language = "English",

volume = "7",

journal = "IEEE Access",

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publisher = "IEEE",

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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

Y1 - 2019/7

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.

KW - Maximum power point trackers

KW - Inverters

KW - Fuzzy logic

KW - Meteorology

KW - Control systems

KW - Artificial neural networks

KW - Particle swarm optimization

KW - ANFIS-ABC

KW - dSPACE

KW - Fuzzy Logic Controller

KW - MPPT

KW - Photovoltaic

KW - SEPIC

KW - ANFIS-ABC

KW - dSPACE

KW - Fuzzy logic controller

KW - MPPT

KW - Photovoltaic

KW - SEPIC

U2 - 10.1109/ACCESS.2019.2931547

DO - 10.1109/ACCESS.2019.2931547

M3 - Journal article

SN - 2169-3536

VL - 7

JO - IEEE Access

JF - IEEE Access

ER -

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

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