A Novel Approach to Achieve MPPT for Photovoltaic System Based SCADA

被引:20
作者
Alhasnawi, Bilal Naji [1 ]
Jasim, Basil H. [2 ]
Alhasnawi, Arshad Naji [3 ]
Sedhom, Bishoy E. [4 ]
Jasim, Ali M. [2 ,5 ]
Khalili, Azam [6 ]
Bures, Vladimir [7 ]
Burgio, Alessandro
Siano, Pierluigi [8 ,9 ]
机构
[1] Imam Jaafar Al Sadiq Univ, Coll Informat Technol, Dept Comp Tech Engn, Al Muthanna 66002, Iraq
[2] Basrah Univ, Elect Engn Dept, Basrah 61001, Iraq
[3] Al Muthanna Univ, Coll Educ Pure Sci, Dept Biol, Samawah 66001, Iraq
[4] Mansoura Univ, Fac Engn, Elect Engn Dept, Mansoura 35516, Egypt
[5] Iraq Univ Coll, Dept Commun Engn, Basrah 61001, Iraq
[6] Malayer Univ, Dept Elect Engn, Malayer 6571995863, Iran
[7] Univ Hradec Kralove, Fac Informat & Management, Hradec Kralove 50003, Czech Republic
[8] Salerno Univ, Management & Innovat Syst Dept, I-84084 Fisciano, Italy
[9] Univ Johannesburg, Dept Elect & Elect Engn Sci, ZA-2006 Johannesburg, South Africa
关键词
MPPT; SCADA; solar system; Internet of Things; POWER POINT TRACKING; PARTICLE SWARM OPTIMIZATION; ENERGY MANAGEMENT-SYSTEM; PV SYSTEM; CUCKOO SEARCH; ALGORITHM; DESIGN; PLATFORM;
D O I
10.3390/en15228480
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
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.
引用
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页数:29
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