Solar Photovoltaic Array Reconfiguration for Optimizing Harvested Power Using an Advanced Artificial Bee Colony Algorithm

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

doi:10.1109/icsse58758.2023.10227209

Solar Photovoltaic Array Reconfiguration for Optimizing Harvested Power Using an Advanced Artificial Bee Colony Algorithm

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

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

3 Citations (Scopus)

Abstract

Exploitation and utilization of electrical energy from solar energy have become popular under the strong technological development of solar photovoltaic (SPV) cells. However, during the power generation process of an SPV array, the efficiency of converting solar energy into electrical energy is significantly affected by natural conditions such as irradiation variation, partial shading, snow, ice, and dust. This paper proposes an advanced artificial bee colony (ABC) algorithm-based reconfiguration approach to overcome these effects as well as to ensure optimal power generation. The proposal-based achievements are compared with those using a genetic algorithm (GA), a particle swarm optimization (PSO) algorithm, and an ABC algorithm to validate the effectiveness of the proposed reconfiguration approach in the performance improvement of the SPV array-based power generation.

Original language	English
Title of host publication	2023 International Conference on System Science and Engineering (ICSSE)
Publisher	IEEE
Pages	406-411
Number of pages	6
ISBN (Electronic)	9798350322941
DOIs	https://doi.org/10.1109/icsse58758.2023.10227209
Publication status	Published - 29 Aug 2023
Event	2023 International Conference on System Science and Engineering - Ho Chi Minh, Viet Nam Duration: 27 Jul 2023 → 28 Jul 2023

Conference

Conference	2023 International Conference on System Science and Engineering
Abbreviated title	ICSSE 2023
Country/Territory	Viet Nam
City	Ho Chi Minh
Period	27/07/23 → 28/07/23

Keywords

artificial bee colony algorithm
harvested power optimization
reconfiguration
solar photovoltaic array

ASJC Scopus subject areas

Artificial Intelligence
Control and Optimization
Energy Engineering and Power Technology
Control and Systems Engineering
Computer Vision and Pattern Recognition
Computer Science Applications

UN SDGs

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

Access to Document

10.1109/icsse58758.2023.10227209

Cite this

@inproceedings{24f4cad7677f4ae8bf8029672f57ee69,

title = "Solar Photovoltaic Array Reconfiguration for Optimizing Harvested Power Using an Advanced Artificial Bee Colony Algorithm",

abstract = "Exploitation and utilization of electrical energy from solar energy have become popular under the strong technological development of solar photovoltaic (SPV) cells. However, during the power generation process of an SPV array, the efficiency of converting solar energy into electrical energy is significantly affected by natural conditions such as irradiation variation, partial shading, snow, ice, and dust. This paper proposes an advanced artificial bee colony (ABC) algorithm-based reconfiguration approach to overcome these effects as well as to ensure optimal power generation. The proposal-based achievements are compared with those using a genetic algorithm (GA), a particle swarm optimization (PSO) algorithm, and an ABC algorithm to validate the effectiveness of the proposed reconfiguration approach in the performance improvement of the SPV array-based power generation.",

keywords = "artificial bee colony algorithm, harvested power optimization, reconfiguration, solar photovoltaic array",

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

year = "2023",

month = aug,

day = "29",

doi = "10.1109/icsse58758.2023.10227209",

language = "English",

pages = "406--411",

booktitle = "2023 International Conference on System Science and Engineering (ICSSE)",

publisher = "IEEE",

address = "United States",

note = "2023 International Conference on System Science and Engineering, ICSSE 2023 ; Conference date: 27-07-2023 Through 28-07-2023",

}

Huynh, DC, Ho, LD, Dunnigan, MW & Barbalata, C 2023, Solar Photovoltaic Array Reconfiguration for Optimizing Harvested Power Using an Advanced Artificial Bee Colony Algorithm. in 2023 International Conference on System Science and Engineering (ICSSE). IEEE, pp. 406-411, 2023 International Conference on System Science and Engineering, Ho Chi Minh, Viet Nam, 27/07/23. https://doi.org/10.1109/icsse58758.2023.10227209

TY - GEN

T1 - Solar Photovoltaic Array Reconfiguration for Optimizing Harvested Power Using an Advanced Artificial Bee Colony Algorithm

AU - Huynh, Duy C.

AU - Ho, Loc D.

AU - Dunnigan, Matthew W.

AU - Barbalata, Corina

PY - 2023/8/29

Y1 - 2023/8/29

N2 - Exploitation and utilization of electrical energy from solar energy have become popular under the strong technological development of solar photovoltaic (SPV) cells. However, during the power generation process of an SPV array, the efficiency of converting solar energy into electrical energy is significantly affected by natural conditions such as irradiation variation, partial shading, snow, ice, and dust. This paper proposes an advanced artificial bee colony (ABC) algorithm-based reconfiguration approach to overcome these effects as well as to ensure optimal power generation. The proposal-based achievements are compared with those using a genetic algorithm (GA), a particle swarm optimization (PSO) algorithm, and an ABC algorithm to validate the effectiveness of the proposed reconfiguration approach in the performance improvement of the SPV array-based power generation.

AB - Exploitation and utilization of electrical energy from solar energy have become popular under the strong technological development of solar photovoltaic (SPV) cells. However, during the power generation process of an SPV array, the efficiency of converting solar energy into electrical energy is significantly affected by natural conditions such as irradiation variation, partial shading, snow, ice, and dust. This paper proposes an advanced artificial bee colony (ABC) algorithm-based reconfiguration approach to overcome these effects as well as to ensure optimal power generation. The proposal-based achievements are compared with those using a genetic algorithm (GA), a particle swarm optimization (PSO) algorithm, and an ABC algorithm to validate the effectiveness of the proposed reconfiguration approach in the performance improvement of the SPV array-based power generation.

KW - artificial bee colony algorithm

KW - harvested power optimization

KW - reconfiguration

KW - solar photovoltaic array

UR - http://www.scopus.com/inward/record.url?scp=85171877026&partnerID=8YFLogxK

U2 - 10.1109/icsse58758.2023.10227209

DO - 10.1109/icsse58758.2023.10227209

M3 - Conference contribution

SP - 406

EP - 411

BT - 2023 International Conference on System Science and Engineering (ICSSE)

PB - IEEE

T2 - 2023 International Conference on System Science and Engineering

Y2 - 27 July 2023 through 28 July 2023

ER -

Solar Photovoltaic Array Reconfiguration for Optimizing Harvested Power Using an Advanced Artificial Bee Colony Algorithm

Abstract

Conference

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this