A comparative study of meta-heuristic and conventional optimization techniques of grid connected photovoltaic system
This paper presents the meta-heuristic and conventional optimizations techniques for the grid connected photovoltaic solar system. The perturb and observe (P&O) and particle swarm optimization (PSO) algorithms are proposed to track the maximum power point (MPP) of the photovoltaic solar system (...
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| Main Authors: | , , |
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2021-12-01.
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| Online Access: | Get Fulltext |
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| LEADER | 02013 am a22003013u 4500 | ||
|---|---|---|---|
| 001 | IJPEDS_21271_13594 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Traore, Mamadou |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Ndiaye, Alphousseyni |e author |
| 700 | 1 | 0 | |a Mbodji, Senghane |e author |
| 245 | 0 | 0 | |a A comparative study of meta-heuristic and conventional optimization techniques of grid connected photovoltaic system |
| 260 | |b Institute of Advanced Engineering and Science, |c 2021-12-01. | ||
| 500 | |a https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/21271 | ||
| 520 | |a This paper presents the meta-heuristic and conventional optimizations techniques for the grid connected photovoltaic solar system. The perturb and observe (P&O) and particle swarm optimization (PSO) algorithms are proposed to track the maximum power point (MPP) of the photovoltaic solar system (PVSS). The regularization of the current supplied into the grid is ensured by the proportional integral (PI) corrector whose parameters are generated by the genetic algorithm (GA). The results of these two MPPT methods are compared and showed that the PSO is more efficient than the P&O. The use of GA algorithm to determine PI parameters allowed to obtain 0.89% of total distortion harmonic (THD). | ||
| 540 | |a Copyright (c) 2021 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-sa/4.0 | ||
| 546 | |a eng | ||
| 690 | |a Renewable energy; PV-Grid system; Optimization algorithm; PI | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n International Journal of Power Electronics and Drive Systems (IJPEDS); Vol 12, No 4: December 2021; 2492-2500 | |
| 786 | 0 | |n 2722-256X | |
| 786 | 0 | |n 2088-8694 | |
| 786 | 0 | |n 10.11591/ijpeds.v12.i4 | |
| 787 | 0 | |n https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/21271/13594 | |
| 856 | 4 | 1 | |u https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/21271/13594 |z Get Fulltext |