Enhancing fuzzy logic MPPT controller with metaheuristic mechanism in photovoltaic system

The conventional fuzzy logic is a deterministic algorithm which means that it will always give the same output when given a particular input. Due to this inherent characteristics, the conventional fuzzy logic might be trapped at local optimum when dealing with a global optimization problem that cons...

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Main Authors: Min Keng Tan, Ronghui He, Qiwen Liu, Min Yang, Kenneth Tze Kin Teo
Format: Proceedings
Language:English
English
Published: IEEE 2019
Subjects:
Online Access:https://eprints.ums.edu.my/id/eprint/31472/1/Enhancing%20fuzzy%20logic%20MPPT%20controller%20with%20metaheuristic%20mechanism%20in%20photovoltaic%20system-ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/31472/2/Enhancing%20fuzzy%20logic%20MPPT%20controller%20with%20metaheuristic%20mechanism%20in%20photovoltaic%20system.pdf
https://eprints.ums.edu.my/id/eprint/31472/
https://ieeexplore.ieee.org/document/8638447
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spelling my.ums.eprints.314722021-12-22T01:04:24Z https://eprints.ums.edu.my/id/eprint/31472/ Enhancing fuzzy logic MPPT controller with metaheuristic mechanism in photovoltaic system Min Keng Tan Ronghui He Qiwen Liu Min Yang Kenneth Tze Kin Teo TK1001-1841 Production of electric energy or power. Powerplants. Central stations The conventional fuzzy logic is a deterministic algorithm which means that it will always give the same output when given a particular input. Due to this inherent characteristics, the conventional fuzzy logic might be trapped at local optimum when dealing with a global optimization problem that consists of several maximum points. As such, this paper aims to explore the potential of improving the fuzzy logic by integrating a greedy or metaheuristic mechanism into it. With the greedy mechanism, the improved fuzzy logic or known as greedy fuzzy logic is given a probability to have a random search for the optimum solution without following the deterministic computation. This mechanism is introduced to prevent the proposed algorithm to be trapped at the local optimum point. The robustness of the proposed algorithm is tested in optimizing a 5x5 photovoltaic (PV) array because the PV array will exhibit multiple peaks when illuminated under a non-uniform irradiance. The existence of multiple peaks will lead to additional difficulties for the conventional maximum power point tracking (MPPT) algorithm in tracking the global maximum power point (MPP) or known as global optimum point. The simulation results show the proposed fuzzy logic with greedy mechanism is able to track the global MPP. IEEE 2019-02-11 Proceedings PeerReviewed text en https://eprints.ums.edu.my/id/eprint/31472/1/Enhancing%20fuzzy%20logic%20MPPT%20controller%20with%20metaheuristic%20mechanism%20in%20photovoltaic%20system-ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/31472/2/Enhancing%20fuzzy%20logic%20MPPT%20controller%20with%20metaheuristic%20mechanism%20in%20photovoltaic%20system.pdf Min Keng Tan and Ronghui He and Qiwen Liu and Min Yang and Kenneth Tze Kin Teo (2019) Enhancing fuzzy logic MPPT controller with metaheuristic mechanism in photovoltaic system. https://ieeexplore.ieee.org/document/8638447
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic TK1001-1841 Production of electric energy or power. Powerplants. Central stations
spellingShingle TK1001-1841 Production of electric energy or power. Powerplants. Central stations
Min Keng Tan
Ronghui He
Qiwen Liu
Min Yang
Kenneth Tze Kin Teo
Enhancing fuzzy logic MPPT controller with metaheuristic mechanism in photovoltaic system
description The conventional fuzzy logic is a deterministic algorithm which means that it will always give the same output when given a particular input. Due to this inherent characteristics, the conventional fuzzy logic might be trapped at local optimum when dealing with a global optimization problem that consists of several maximum points. As such, this paper aims to explore the potential of improving the fuzzy logic by integrating a greedy or metaheuristic mechanism into it. With the greedy mechanism, the improved fuzzy logic or known as greedy fuzzy logic is given a probability to have a random search for the optimum solution without following the deterministic computation. This mechanism is introduced to prevent the proposed algorithm to be trapped at the local optimum point. The robustness of the proposed algorithm is tested in optimizing a 5x5 photovoltaic (PV) array because the PV array will exhibit multiple peaks when illuminated under a non-uniform irradiance. The existence of multiple peaks will lead to additional difficulties for the conventional maximum power point tracking (MPPT) algorithm in tracking the global maximum power point (MPP) or known as global optimum point. The simulation results show the proposed fuzzy logic with greedy mechanism is able to track the global MPP.
format Proceedings
author Min Keng Tan
Ronghui He
Qiwen Liu
Min Yang
Kenneth Tze Kin Teo
author_facet Min Keng Tan
Ronghui He
Qiwen Liu
Min Yang
Kenneth Tze Kin Teo
author_sort Min Keng Tan
title Enhancing fuzzy logic MPPT controller with metaheuristic mechanism in photovoltaic system
title_short Enhancing fuzzy logic MPPT controller with metaheuristic mechanism in photovoltaic system
title_full Enhancing fuzzy logic MPPT controller with metaheuristic mechanism in photovoltaic system
title_fullStr Enhancing fuzzy logic MPPT controller with metaheuristic mechanism in photovoltaic system
title_full_unstemmed Enhancing fuzzy logic MPPT controller with metaheuristic mechanism in photovoltaic system
title_sort enhancing fuzzy logic mppt controller with metaheuristic mechanism in photovoltaic system
publisher IEEE
publishDate 2019
url https://eprints.ums.edu.my/id/eprint/31472/1/Enhancing%20fuzzy%20logic%20MPPT%20controller%20with%20metaheuristic%20mechanism%20in%20photovoltaic%20system-ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/31472/2/Enhancing%20fuzzy%20logic%20MPPT%20controller%20with%20metaheuristic%20mechanism%20in%20photovoltaic%20system.pdf
https://eprints.ums.edu.my/id/eprint/31472/
https://ieeexplore.ieee.org/document/8638447
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score 13.18916