A Hybrid Maximum Power Point Tracking Method for Photovoltaic Systems for Dynamic Weather Conditions

A hybrid MPPT (maximum power point tracking) controller integrates FLC (fuzzy logic controller) and P&O (Perturbation and Observation) method for MMPT of PV (Photovoltaic) under dynamic weather conditions is proposed. An adaptive neuro-fuzzy inference system is used to optimize parameters an...

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Main Authors: Khaled Bataineh, Naser Eid
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Resources
Subjects:
Online Access:https://www.mdpi.com/2079-9276/7/4/68
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spelling doaj-a278142ec664491cbf824892065ee8b62020-11-24T22:52:09ZengMDPI AGResources2079-92762018-11-01746810.3390/resources7040068resources7040068A Hybrid Maximum Power Point Tracking Method for Photovoltaic Systems for Dynamic Weather ConditionsKhaled Bataineh0Naser Eid1Department of Mechanical Engineering, Jordan University of Science and Technology, Irbid 22110, JordanDepartment of Mechanical Engineering, Jordan University of Science and Technology, Irbid 22110, JordanA hybrid MPPT (maximum power point tracking) controller integrates FLC (fuzzy logic controller) and P&O (Perturbation and Observation) method for MMPT of PV (Photovoltaic) under dynamic weather conditions is proposed. An adaptive neuro-fuzzy inference system is used to optimize parameters and membership functions of FLC. FLC is used to find the region of MPP (maximum power point); then, P&O technique is employed to accurately track the MPP. MATLAB/Simulink models are built to evaluate the performance of the proposed hybrid algorithm. In order to validate the performance of the proposed algorithm, comparisons with standalone FLC and P&O are carried out. The performance of the proposed algorithm is tested against dynamic weather condition. The results showed that the proposed algorithm successfully improve the dynamic and steady state responses of PV under severe dynamic weather condition. More specifically, the proposed approach shows its capability to attain the MPP faster than P&O and provided higher power than the standalone FLC. Finally, the proposed algorithm overcomes the limitations associated with FLC and P&O.https://www.mdpi.com/2079-9276/7/4/68A hybrid MPPTPartial shadingPhotovoltaicANFIS
collection DOAJ
language English
format Article
sources DOAJ
author Khaled Bataineh
Naser Eid
spellingShingle Khaled Bataineh
Naser Eid
A Hybrid Maximum Power Point Tracking Method for Photovoltaic Systems for Dynamic Weather Conditions
Resources
A hybrid MPPT
Partial shading
Photovoltaic
ANFIS
author_facet Khaled Bataineh
Naser Eid
author_sort Khaled Bataineh
title A Hybrid Maximum Power Point Tracking Method for Photovoltaic Systems for Dynamic Weather Conditions
title_short A Hybrid Maximum Power Point Tracking Method for Photovoltaic Systems for Dynamic Weather Conditions
title_full A Hybrid Maximum Power Point Tracking Method for Photovoltaic Systems for Dynamic Weather Conditions
title_fullStr A Hybrid Maximum Power Point Tracking Method for Photovoltaic Systems for Dynamic Weather Conditions
title_full_unstemmed A Hybrid Maximum Power Point Tracking Method for Photovoltaic Systems for Dynamic Weather Conditions
title_sort hybrid maximum power point tracking method for photovoltaic systems for dynamic weather conditions
publisher MDPI AG
series Resources
issn 2079-9276
publishDate 2018-11-01
description A hybrid MPPT (maximum power point tracking) controller integrates FLC (fuzzy logic controller) and P&O (Perturbation and Observation) method for MMPT of PV (Photovoltaic) under dynamic weather conditions is proposed. An adaptive neuro-fuzzy inference system is used to optimize parameters and membership functions of FLC. FLC is used to find the region of MPP (maximum power point); then, P&O technique is employed to accurately track the MPP. MATLAB/Simulink models are built to evaluate the performance of the proposed hybrid algorithm. In order to validate the performance of the proposed algorithm, comparisons with standalone FLC and P&O are carried out. The performance of the proposed algorithm is tested against dynamic weather condition. The results showed that the proposed algorithm successfully improve the dynamic and steady state responses of PV under severe dynamic weather condition. More specifically, the proposed approach shows its capability to attain the MPP faster than P&O and provided higher power than the standalone FLC. Finally, the proposed algorithm overcomes the limitations associated with FLC and P&O.
topic A hybrid MPPT
Partial shading
Photovoltaic
ANFIS
url https://www.mdpi.com/2079-9276/7/4/68
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