Optimization of Large-Scale Solar Panels Distribution Using Genetic Algorithm

Shamma Al Neyadi; Mariam Al Kuwaiti; Shaikha Al Daheri; Maitha Al Marzroei; Ahayed Al Ketbi; Fady Alnajjar

doi:10.1109/MENA-SC54044.2023.10374524

Optimization of Large-Scale Solar Panels Distribution Using Genetic Algorithm

Shamma Al Neyadi
, Mariam Al Kuwaiti
, Shaikha Al Daheri
, Maitha Al Marzroei
, Ahayed Al Ketbi
, Fady Alnajjar

Department of Computer Science and Software Engineering

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

3 Citations (Scopus)

Abstract

Renewable energy is rapidly growing, and solar power systems are a significant contributor. By 2050, the UAE aims to generate 50% of electric energy from carbon-free sources such as solar photovoltaic (PV). PV panel system's maximum output power varies over time, depending on external elements such as the sun's radiation, the surrounding temperature, dust, wind, etc., which is highly associated with the panel positioning. As of now, there is no well-defined methodology for determining the optimal distribution and positioning of large-scale solar panels to maximize energy output. To tackle this issue, our research investigates the impact of solar panel positioning and distribution on energy efficiency using a Genetic Algorithm (GA). GA is an optimization technique inspired by the principles of natural selection and genetics, known for its effectiveness in solving intricate problems across various domains. We anticipate that this study will contribute to the optimization of distribution and positioning in large-scale solar power plants, ultimately enhancing their performance.

Original language	English
Title of host publication	2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665491464
DOIs	https://doi.org/10.1109/MENA-SC54044.2023.10374524
Publication status	Published - 2023
Event	1st Middle East and North Africa Solar Conference, MENA-SC 2023 - Dubai, United Arab Emirates Duration: Nov 15 2023 → Nov 18 2023

Publication series

Name	2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings

Conference

Conference	1st Middle East and North Africa Solar Conference, MENA-SC 2023
Country/Territory	United Arab Emirates
City	Dubai
Period	11/15/23 → 11/18/23

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Genetic Algorithm
PV system
Renewable energy
Solar Panel positioning

ASJC Scopus subject areas

Energy Engineering and Power Technology
Renewable Energy, Sustainability and the Environment
Electronic, Optical and Magnetic Materials
Surfaces, Coatings and Films

Access to Document

10.1109/MENA-SC54044.2023.10374524

Cite this

Al Neyadi, S., Al Kuwaiti, M., Al Daheri, S., Al Marzroei, M., Al Ketbi, A., & Alnajjar, F. (2023). Optimization of Large-Scale Solar Panels Distribution Using Genetic Algorithm. In 2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings (2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MENA-SC54044.2023.10374524

Optimization of Large-Scale Solar Panels Distribution Using Genetic Algorithm. / Al Neyadi, Shamma; Al Kuwaiti, Mariam; Al Daheri, Shaikha et al.
2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings).

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

Al Neyadi, S, Al Kuwaiti, M, Al Daheri, S, Al Marzroei, M, Al Ketbi, A & Alnajjar, F 2023, Optimization of Large-Scale Solar Panels Distribution Using Genetic Algorithm. in 2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings. 2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 1st Middle East and North Africa Solar Conference, MENA-SC 2023, Dubai, United Arab Emirates, 11/15/23. https://doi.org/10.1109/MENA-SC54044.2023.10374524

Al Neyadi S, Al Kuwaiti M, Al Daheri S, Al Marzroei M, Al Ketbi A, Alnajjar F. Optimization of Large-Scale Solar Panels Distribution Using Genetic Algorithm. In 2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings). doi: 10.1109/MENA-SC54044.2023.10374524

Al Neyadi, Shamma ; Al Kuwaiti, Mariam ; Al Daheri, Shaikha et al. / Optimization of Large-Scale Solar Panels Distribution Using Genetic Algorithm. 2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings).

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abstract = "Renewable energy is rapidly growing, and solar power systems are a significant contributor. By 2050, the UAE aims to generate 50\% of electric energy from carbon-free sources such as solar photovoltaic (PV). PV panel system's maximum output power varies over time, depending on external elements such as the sun's radiation, the surrounding temperature, dust, wind, etc., which is highly associated with the panel positioning. As of now, there is no well-defined methodology for determining the optimal distribution and positioning of large-scale solar panels to maximize energy output. To tackle this issue, our research investigates the impact of solar panel positioning and distribution on energy efficiency using a Genetic Algorithm (GA). GA is an optimization technique inspired by the principles of natural selection and genetics, known for its effectiveness in solving intricate problems across various domains. We anticipate that this study will contribute to the optimization of distribution and positioning in large-scale solar power plants, ultimately enhancing their performance.",

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AU - Al Kuwaiti, Mariam

AU - Al Daheri, Shaikha

AU - Al Marzroei, Maitha

AU - Al Ketbi, Ahayed

AU - Alnajjar, Fady

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AB - Renewable energy is rapidly growing, and solar power systems are a significant contributor. By 2050, the UAE aims to generate 50% of electric energy from carbon-free sources such as solar photovoltaic (PV). PV panel system's maximum output power varies over time, depending on external elements such as the sun's radiation, the surrounding temperature, dust, wind, etc., which is highly associated with the panel positioning. As of now, there is no well-defined methodology for determining the optimal distribution and positioning of large-scale solar panels to maximize energy output. To tackle this issue, our research investigates the impact of solar panel positioning and distribution on energy efficiency using a Genetic Algorithm (GA). GA is an optimization technique inspired by the principles of natural selection and genetics, known for its effectiveness in solving intricate problems across various domains. We anticipate that this study will contribute to the optimization of distribution and positioning in large-scale solar power plants, ultimately enhancing their performance.

KW - Genetic Algorithm

KW - PV system

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ER -

Optimization of Large-Scale Solar Panels Distribution Using Genetic Algorithm

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this