Maximum power point tracking of partially shading pv system using particle swarm optimization

S. Obukhov, A. Ibrahim, Raef Aboelsaud

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

The partial shading condition (PSC) often occur in large photovoltaic (PV) generation system (PGS), it causes system losses and many problems in reliability of power system. The power voltage ( p-v) curve under the PSC have more peaks local and global peak and this makes the track of maximum power is very difficult and the conventional algorithms can't track the global maximum power point in this case. In this paper, the maximum power point tracking (MPPT) under PSC are evaluated using the particle swarm optimization (PSO). The proposed model tracks the global maximum power point (GMPP) very fast and in very short time and don't exceed 30 iterations under minimum solar irradiation cases.

Original languageEnglish
Title of host publicationProceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018
PublisherAssociation for Computing Machinery
Pages161-165
Number of pages5
ISBN (Print)9781450364720
DOIs
Publication statusPublished - 25 Jun 2018
Event4th International Conference on Frontiers of Educational Technologies, ICFET 2018, Jointly with its Workshop the 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018 - Moscow, Russian Federation
Duration: 25 Jun 201827 Jun 2018

Conference

Conference4th International Conference on Frontiers of Educational Technologies, ICFET 2018, Jointly with its Workshop the 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018
CountryRussian Federation
CityMoscow
Period25.6.1827.6.18

Fingerprint

Particle swarm optimization (PSO)
Irradiation
Electric potential

Keywords

  • Global maximum power point (GMPP)
  • Maximum power point tracking (MPPT)
  • Partially shading condition (PSC)
  • Particle swarm optimization (PSO)

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Obukhov, S., Ibrahim, A., & Aboelsaud, R. (2018). Maximum power point tracking of partially shading pv system using particle swarm optimization. In Proceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018 (pp. 161-165). Association for Computing Machinery. https://doi.org/10.1145/3233347.3233375

Maximum power point tracking of partially shading pv system using particle swarm optimization. / Obukhov, S.; Ibrahim, A.; Aboelsaud, Raef.

Proceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018. Association for Computing Machinery, 2018. p. 161-165.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Obukhov, S, Ibrahim, A & Aboelsaud, R 2018, Maximum power point tracking of partially shading pv system using particle swarm optimization. in Proceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018. Association for Computing Machinery, pp. 161-165, 4th International Conference on Frontiers of Educational Technologies, ICFET 2018, Jointly with its Workshop the 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018, Moscow, Russian Federation, 25.6.18. https://doi.org/10.1145/3233347.3233375
Obukhov S, Ibrahim A, Aboelsaud R. Maximum power point tracking of partially shading pv system using particle swarm optimization. In Proceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018. Association for Computing Machinery. 2018. p. 161-165 https://doi.org/10.1145/3233347.3233375
Obukhov, S. ; Ibrahim, A. ; Aboelsaud, Raef. / Maximum power point tracking of partially shading pv system using particle swarm optimization. Proceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018. Association for Computing Machinery, 2018. pp. 161-165
@inproceedings{c44b9fe7de7d45c5adbe003a729acb5d,
title = "Maximum power point tracking of partially shading pv system using particle swarm optimization",
abstract = "The partial shading condition (PSC) often occur in large photovoltaic (PV) generation system (PGS), it causes system losses and many problems in reliability of power system. The power voltage ( p-v) curve under the PSC have more peaks local and global peak and this makes the track of maximum power is very difficult and the conventional algorithms can't track the global maximum power point in this case. In this paper, the maximum power point tracking (MPPT) under PSC are evaluated using the particle swarm optimization (PSO). The proposed model tracks the global maximum power point (GMPP) very fast and in very short time and don't exceed 30 iterations under minimum solar irradiation cases.",
keywords = "Global maximum power point (GMPP), Maximum power point tracking (MPPT), Partially shading condition (PSC), Particle swarm optimization (PSO)",
author = "S. Obukhov and A. Ibrahim and Raef Aboelsaud",
year = "2018",
month = "6",
day = "25",
doi = "10.1145/3233347.3233375",
language = "English",
isbn = "9781450364720",
pages = "161--165",
booktitle = "Proceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018",
publisher = "Association for Computing Machinery",

}

TY - GEN

T1 - Maximum power point tracking of partially shading pv system using particle swarm optimization

AU - Obukhov, S.

AU - Ibrahim, A.

AU - Aboelsaud, Raef

PY - 2018/6/25

Y1 - 2018/6/25

N2 - The partial shading condition (PSC) often occur in large photovoltaic (PV) generation system (PGS), it causes system losses and many problems in reliability of power system. The power voltage ( p-v) curve under the PSC have more peaks local and global peak and this makes the track of maximum power is very difficult and the conventional algorithms can't track the global maximum power point in this case. In this paper, the maximum power point tracking (MPPT) under PSC are evaluated using the particle swarm optimization (PSO). The proposed model tracks the global maximum power point (GMPP) very fast and in very short time and don't exceed 30 iterations under minimum solar irradiation cases.

AB - The partial shading condition (PSC) often occur in large photovoltaic (PV) generation system (PGS), it causes system losses and many problems in reliability of power system. The power voltage ( p-v) curve under the PSC have more peaks local and global peak and this makes the track of maximum power is very difficult and the conventional algorithms can't track the global maximum power point in this case. In this paper, the maximum power point tracking (MPPT) under PSC are evaluated using the particle swarm optimization (PSO). The proposed model tracks the global maximum power point (GMPP) very fast and in very short time and don't exceed 30 iterations under minimum solar irradiation cases.

KW - Global maximum power point (GMPP)

KW - Maximum power point tracking (MPPT)

KW - Partially shading condition (PSC)

KW - Particle swarm optimization (PSO)

UR - http://www.scopus.com/inward/record.url?scp=85054813432&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85054813432&partnerID=8YFLogxK

U2 - 10.1145/3233347.3233375

DO - 10.1145/3233347.3233375

M3 - Conference contribution

SN - 9781450364720

SP - 161

EP - 165

BT - Proceedings of 2018 the 4th International Conference on Frontiers of Educational Technologies, ICFET 2018 - Workshop 2018 3rd International Conference on Knowledge Engineering and Applications, ICKEA 2018

PB - Association for Computing Machinery

ER -