Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm

Duy C. Huynh; Loc D. Ho; Matthew W. Dunnigan

doi:10.1007/978-3-030-62324-1_24

Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm

Duy C. Huynh, Loc D. Ho, Matthew W. Dunnigan

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

Abstract

The solar photovoltaic (PV) array is one of the main components of the solar PV system. The accuracy of the solar PV cell parameters and models is directly affected to the operation and control of the solar PV system. It is obvious that the solar PV cell parameters may change with various operation conditions. Thus, it is important to estimate parameters of the solar PV cell model. Due to the non-linearity, multivariable and multimodal features of the solar PV cell model, the existing approaches are incapable to estimate parameters of the solar PV cell model with a high accuracy. This paper proposes an improved artificial bee colony (ABC) algorithm for estimating parameters of the solar PV cell model. The estimation results obtained by using the improved ABC algorithm are promising and better than those found by other existing approaches.

Original language	English
Title of host publication	Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020
Editors	Yo-Ping Huang, Wen-June Wang, Hoang An Quoc, Le Hieu Giang, Nguyen-Le Hung
Publisher	Springer
Pages	281-292
Number of pages	12
ISBN (Electronic)	9783030623241
ISBN (Print)	9783030623234
DOIs	https://doi.org/10.1007/978-3-030-62324-1_24
Publication status	Published - 2021
Event	5th International Conference on Green Technology and Sustainable Development 2020 - Da Nang City, Viet Nam Duration: 27 Nov 2020 → 28 Nov 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1284
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	5th International Conference on Green Technology and Sustainable Development 2020
Abbreviated title	GTSD 2020
Country	Viet Nam
City	Da Nang City
Period	27/11/20 → 28/11/20

Keywords

Artificial bee colony algorithm
Parameter estimation
Solar photovoltaic cell

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science(all)

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

Access to Document

10.1007/978-3-030-62324-1_24

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Huynh, D. C., Ho, L. D., & Dunnigan, M. W. (2021). Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm. In Y-P. Huang, W-J. Wang, H. A. Quoc, L. H. Giang, & N-L. Hung (Eds.), Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020 (pp. 281-292). (Advances in Intelligent Systems and Computing; Vol. 1284). Springer. https://doi.org/10.1007/978-3-030-62324-1_24

Huynh, Duy C. ; Ho, Loc D. ; Dunnigan, Matthew W. / Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm. Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020. editor / Yo-Ping Huang ; Wen-June Wang ; Hoang An Quoc ; Le Hieu Giang ; Nguyen-Le Hung. Springer, 2021. pp. 281-292 (Advances in Intelligent Systems and Computing).

@inproceedings{2b1c78e2cd0946189989e6dec6f22858,

title = "Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm",

abstract = "The solar photovoltaic (PV) array is one of the main components of the solar PV system. The accuracy of the solar PV cell parameters and models is directly affected to the operation and control of the solar PV system. It is obvious that the solar PV cell parameters may change with various operation conditions. Thus, it is important to estimate parameters of the solar PV cell model. Due to the non-linearity, multivariable and multimodal features of the solar PV cell model, the existing approaches are incapable to estimate parameters of the solar PV cell model with a high accuracy. This paper proposes an improved artificial bee colony (ABC) algorithm for estimating parameters of the solar PV cell model. The estimation results obtained by using the improved ABC algorithm are promising and better than those found by other existing approaches.",

keywords = "Artificial bee colony algorithm, Parameter estimation, Solar photovoltaic cell",

author = "Huynh, {Duy C.} and Ho, {Loc D.} and Dunnigan, {Matthew W.}",

year = "2021",

doi = "10.1007/978-3-030-62324-1_24",

language = "English",

isbn = "9783030623234",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "281--292",

editor = "Yo-Ping Huang and Wen-June Wang and Quoc, {Hoang An} and Giang, {Le Hieu} and Nguyen-Le Hung",

booktitle = "Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020",

note = "5th International Conference on Green Technology and Sustainable Development 2020, GTSD 2020 ; Conference date: 27-11-2020 Through 28-11-2020",

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Huynh, DC, Ho, LD & Dunnigan, MW 2021, Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm. in Y-P Huang, W-J Wang, HA Quoc, LH Giang & N-L Hung (eds), Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020. Advances in Intelligent Systems and Computing, vol. 1284, Springer, pp. 281-292, 5th International Conference on Green Technology and Sustainable Development 2020, Da Nang City, Viet Nam, 27/11/20. https://doi.org/10.1007/978-3-030-62324-1_24

Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm. / Huynh, Duy C.; Ho, Loc D.; Dunnigan, Matthew W.

Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020. ed. / Yo-Ping Huang; Wen-June Wang; Hoang An Quoc; Le Hieu Giang; Nguyen-Le Hung. Springer, 2021. p. 281-292 (Advances in Intelligent Systems and Computing; Vol. 1284).

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

TY - GEN

T1 - Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm

AU - Huynh, Duy C.

AU - Ho, Loc D.

AU - Dunnigan, Matthew W.

PY - 2021

Y1 - 2021

N2 - The solar photovoltaic (PV) array is one of the main components of the solar PV system. The accuracy of the solar PV cell parameters and models is directly affected to the operation and control of the solar PV system. It is obvious that the solar PV cell parameters may change with various operation conditions. Thus, it is important to estimate parameters of the solar PV cell model. Due to the non-linearity, multivariable and multimodal features of the solar PV cell model, the existing approaches are incapable to estimate parameters of the solar PV cell model with a high accuracy. This paper proposes an improved artificial bee colony (ABC) algorithm for estimating parameters of the solar PV cell model. The estimation results obtained by using the improved ABC algorithm are promising and better than those found by other existing approaches.

AB - The solar photovoltaic (PV) array is one of the main components of the solar PV system. The accuracy of the solar PV cell parameters and models is directly affected to the operation and control of the solar PV system. It is obvious that the solar PV cell parameters may change with various operation conditions. Thus, it is important to estimate parameters of the solar PV cell model. Due to the non-linearity, multivariable and multimodal features of the solar PV cell model, the existing approaches are incapable to estimate parameters of the solar PV cell model with a high accuracy. This paper proposes an improved artificial bee colony (ABC) algorithm for estimating parameters of the solar PV cell model. The estimation results obtained by using the improved ABC algorithm are promising and better than those found by other existing approaches.

KW - Artificial bee colony algorithm

KW - Parameter estimation

KW - Solar photovoltaic cell

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U2 - 10.1007/978-3-030-62324-1_24

DO - 10.1007/978-3-030-62324-1_24

M3 - Conference contribution

AN - SCOPUS:85096600003

SN - 9783030623234

T3 - Advances in Intelligent Systems and Computing

SP - 281

EP - 292

BT - Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020

A2 - Huang, Yo-Ping

A2 - Wang, Wen-June

A2 - Quoc, Hoang An

A2 - Giang, Le Hieu

A2 - Hung, Nguyen-Le

PB - Springer

T2 - 5th International Conference on Green Technology and Sustainable Development 2020

Y2 - 27 November 2020 through 28 November 2020

ER -

Huynh DC, Ho LD, Dunnigan MW. Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm. In Huang Y-P, Wang W-J, Quoc HA, Giang LH, Hung N-L, editors, Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020. Springer. 2021. p. 281-292. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-030-62324-1_24

Parameter Estimation of Solar Photovoltaic Cells Using an Improved Artificial Bee Colony Algorithm

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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