ANN-PSO Optimization of PV Systems under Different Weather Conditions

Adedayo M. Farayola; Yanxia Sun; Ahmed Ali

doi:10.1109/ICRERA.2018.8566974

ANN-PSO Optimization of PV Systems under Different Weather Conditions

Adedayo M. Farayola
, Yanxia Sun
, Ahmed Ali

University of Johannesburg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

31 Citations (Scopus)

Abstract

Conventional maximum power point tracking (MPPT) techniques like Perturb 0bserve perform ineffectively under partial shading condition due to its inability to effectively track the global maximum power point (GMPP). Particle swarm optimization (PSO) is a recent metaheuristic technique and has been used to extract maximum power from PV systems but takes time to iteratively locate the GMPP. This paper presents a novel hybrid ANN-PSO technique using series-connected distributed MPPT configuration. The simulation MPPT results using ANN- PSO configuration, PSO, and Perturb observe (P O) were compared with theoretical power values under different weather conditions to determine the most efficient MPPT method that can be considered for MPPT task in PV systems under uniform irradiance and partial shading conditions. Obtained results show that ANN-PSO can achieve the best performance.

Original language	English
Title of host publication	7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1363-1368
Number of pages	6
ISBN (Electronic)	9781538659823
DOIs	https://doi.org/10.1109/ICRERA.2018.8566974
Publication status	Published - 6 Dec 2018
Event	7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018 - Paris, France Duration: 14 Oct 2018 → 17 Oct 2018

Publication series

Name	7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018

Conference

Conference	7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018
Country/Territory	France
City	Paris
Period	14/10/18 → 17/10/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

ANN-PSO
Distributed MPPT
Global MPPT
MPPT
P O
PSO
Partial shading
Photovoltaic systems

ASJC Scopus subject areas

Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering

Access to Document

10.1109/ICRERA.2018.8566974

Cite this

Farayola, A. M., Sun, Y., & Ali, A. (2018). ANN-PSO Optimization of PV Systems under Different Weather Conditions. In 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018 (pp. 1363-1368). Article 8566974 (7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRERA.2018.8566974

Farayola, Adedayo M. ; Sun, Yanxia ; Ali, Ahmed. / ANN-PSO Optimization of PV Systems under Different Weather Conditions. 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1363-1368 (7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018).

@inproceedings{e151233c48be4ee683d22a0ed10d54bf,

title = "ANN-PSO Optimization of PV Systems under Different Weather Conditions",

abstract = "Conventional maximum power point tracking (MPPT) techniques like Perturb 0bserve perform ineffectively under partial shading condition due to its inability to effectively track the global maximum power point (GMPP). Particle swarm optimization (PSO) is a recent metaheuristic technique and has been used to extract maximum power from PV systems but takes time to iteratively locate the GMPP. This paper presents a novel hybrid ANN-PSO technique using series-connected distributed MPPT configuration. The simulation MPPT results using ANN- PSO configuration, PSO, and Perturb observe (P O) were compared with theoretical power values under different weather conditions to determine the most efficient MPPT method that can be considered for MPPT task in PV systems under uniform irradiance and partial shading conditions. Obtained results show that ANN-PSO can achieve the best performance.",

keywords = "ANN-PSO, Distributed MPPT, Global MPPT, MPPT, P O, PSO, Partial shading, Photovoltaic systems",

author = "Farayola, \{Adedayo M.\} and Yanxia Sun and Ahmed Ali",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018 ; Conference date: 14-10-2018 Through 17-10-2018",

year = "2018",

month = dec,

day = "6",

doi = "10.1109/ICRERA.2018.8566974",

language = "English",

series = "7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1363--1368",

booktitle = "7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018",

address = "United States",

}

Farayola, AM, Sun, Y & Ali, A 2018, ANN-PSO Optimization of PV Systems under Different Weather Conditions. in 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018., 8566974, 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1363-1368, 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018, Paris, France, 14/10/18. https://doi.org/10.1109/ICRERA.2018.8566974

ANN-PSO Optimization of PV Systems under Different Weather Conditions. / Farayola, Adedayo M.; Sun, Yanxia ; Ali, Ahmed.
7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1363-1368 8566974 (7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - ANN-PSO Optimization of PV Systems under Different Weather Conditions

AU - Farayola, Adedayo M.

AU - Sun, Yanxia

AU - Ali, Ahmed

PY - 2018/12/6

Y1 - 2018/12/6

N2 - Conventional maximum power point tracking (MPPT) techniques like Perturb 0bserve perform ineffectively under partial shading condition due to its inability to effectively track the global maximum power point (GMPP). Particle swarm optimization (PSO) is a recent metaheuristic technique and has been used to extract maximum power from PV systems but takes time to iteratively locate the GMPP. This paper presents a novel hybrid ANN-PSO technique using series-connected distributed MPPT configuration. The simulation MPPT results using ANN- PSO configuration, PSO, and Perturb observe (P O) were compared with theoretical power values under different weather conditions to determine the most efficient MPPT method that can be considered for MPPT task in PV systems under uniform irradiance and partial shading conditions. Obtained results show that ANN-PSO can achieve the best performance.

AB - Conventional maximum power point tracking (MPPT) techniques like Perturb 0bserve perform ineffectively under partial shading condition due to its inability to effectively track the global maximum power point (GMPP). Particle swarm optimization (PSO) is a recent metaheuristic technique and has been used to extract maximum power from PV systems but takes time to iteratively locate the GMPP. This paper presents a novel hybrid ANN-PSO technique using series-connected distributed MPPT configuration. The simulation MPPT results using ANN- PSO configuration, PSO, and Perturb observe (P O) were compared with theoretical power values under different weather conditions to determine the most efficient MPPT method that can be considered for MPPT task in PV systems under uniform irradiance and partial shading conditions. Obtained results show that ANN-PSO can achieve the best performance.

KW - ANN-PSO

KW - Distributed MPPT

KW - Global MPPT

KW - MPPT

KW - P O

KW - PSO

KW - Partial shading

KW - Photovoltaic systems

UR - https://www.scopus.com/pages/publications/85060619971

U2 - 10.1109/ICRERA.2018.8566974

DO - 10.1109/ICRERA.2018.8566974

M3 - Conference contribution

AN - SCOPUS:85060619971

T3 - 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018

SP - 1363

EP - 1368

BT - 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018

Y2 - 14 October 2018 through 17 October 2018

ER -

Farayola AM, Sun Y , Ali A. ANN-PSO Optimization of PV Systems under Different Weather Conditions. In 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1363-1368. 8566974. (7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018). doi: 10.1109/ICRERA.2018.8566974

ANN-PSO Optimization of PV Systems under Different Weather Conditions

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this