LAPSE:2023.7843
Published Article
LAPSE:2023.7843
A Novel Approach to Achieve MPPT for Photovoltaic System Based SCADA
February 24, 2023
Abstract
In this study, an improved artificial intelligence algorithms augmented Internet of Things (IoT)-based maximum power point tracking (MPPT) for photovoltaic (PV) system has been proposed. This will facilitate preventive maintenance, fault detection, and historical analysis of the plant in addition to real-time monitoring. Further, the simulation results validate the improved performance of the suggested method. To demonstrate the superiority of the proposed MPPT algorithm over current methods, such as cuckoo search algorithms and the incremental conductance approach, a performance comparison is offered. The outcomes demonstrate the suggested algorithm’s capability to track the Global Maximum Power Point (GMPP) with quicker convergence and less power oscillations than before. The results clearly show that the artificial intelligence algorithm-based MPPT is capable of tracking the GMPP with an average efficiency of 88%, and an average tracking time of 0.029 s, proving both its viability and effectiveness.
In this study, an improved artificial intelligence algorithms augmented Internet of Things (IoT)-based maximum power point tracking (MPPT) for photovoltaic (PV) system has been proposed. This will facilitate preventive maintenance, fault detection, and historical analysis of the plant in addition to real-time monitoring. Further, the simulation results validate the improved performance of the suggested method. To demonstrate the superiority of the proposed MPPT algorithm over current methods, such as cuckoo search algorithms and the incremental conductance approach, a performance comparison is offered. The outcomes demonstrate the suggested algorithm’s capability to track the Global Maximum Power Point (GMPP) with quicker convergence and less power oscillations than before. The results clearly show that the artificial intelligence algorithm-based MPPT is capable of tracking the GMPP with an average efficiency of 88%, and an average tracking time of 0.029 s, proving both its viability and effectiveness.
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Keywords
Internet of Things, MPPT, SCADA, solar system
Subject
Suggested Citation
Alhasnawi BN, Jasim BH, Alhasnawi AN, Sedhom BE, Jasim AM, Khalili A, Bureš V, Burgio A, Siano P. A Novel Approach to Achieve MPPT for Photovoltaic System Based SCADA. (2023). LAPSE:2023.7843
Author Affiliations
Alhasnawi BN: Department of Computer Technical Engineering, College of Information Technology, Imam Ja’afar Al-Sadiq University, Al-Muthanna 66002, Iraq [ORCID]
Jasim BH: Electrical Engineering Department, Basrah University, Basrah 61001, Iraq [ORCID]
Alhasnawi AN: Department of Biology, College of Education for Pure Sciences, Al-Muthanna University, Samawah 66001, Iraq
Sedhom BE: Electrical Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt [ORCID]
Jasim AM: Electrical Engineering Department, Basrah University, Basrah 61001, Iraq; Department of Communications Engineering, Iraq University College, Basrah 61001, Iraq [ORCID]
Khalili A: Department of Electrical Engineering, Malayer University, Malayer 65719-95863, Iran
Bureš V: Faculty of Informatics and Management, University of Hradec Králové, 50003 Hradec Králové, Czech Republic [ORCID]
Burgio A: Independent Researcher, 20124 Milano, Italy [ORCID]
Siano P: Management and Innovation Systems Department, Salerno University, 84084 Fisciano, Italy; Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa [ORCID]
Jasim BH: Electrical Engineering Department, Basrah University, Basrah 61001, Iraq [ORCID]
Alhasnawi AN: Department of Biology, College of Education for Pure Sciences, Al-Muthanna University, Samawah 66001, Iraq
Sedhom BE: Electrical Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt [ORCID]
Jasim AM: Electrical Engineering Department, Basrah University, Basrah 61001, Iraq; Department of Communications Engineering, Iraq University College, Basrah 61001, Iraq [ORCID]
Khalili A: Department of Electrical Engineering, Malayer University, Malayer 65719-95863, Iran
Bureš V: Faculty of Informatics and Management, University of Hradec Králové, 50003 Hradec Králové, Czech Republic [ORCID]
Burgio A: Independent Researcher, 20124 Milano, Italy [ORCID]
Siano P: Management and Innovation Systems Department, Salerno University, 84084 Fisciano, Italy; Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa [ORCID]
Journal Name
Energies
Volume
15
Issue
22
First Page
8480
Year
2022
Publication Date
2022-11-13
ISSN
1996-1073
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PII: en15228480, Publication Type: Journal Article
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LAPSE:2023.7843
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https://doi.org/10.3390/en15228480
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Feb 24, 2023
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