TY - GEN
T1 - Optimization of Large-Scale Solar Panels Distribution Using Genetic Algorithm
AU - Al Neyadi, Shamma
AU - Al Kuwaiti, Mariam
AU - Al Daheri, Shaikha
AU - Al Marzroei, Maitha
AU - Al Ketbi, Ahayed
AU - Alnajjar, Fady
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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.
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
KW - Renewable energy
KW - Solar Panel positioning
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U2 - 10.1109/MENA-SC54044.2023.10374524
DO - 10.1109/MENA-SC54044.2023.10374524
M3 - Conference contribution
AN - SCOPUS:85183472647
T3 - 2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings
BT - 2023 Middle East and North Africa Solar Conference, MENA-SC 2023 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st Middle East and North Africa Solar Conference, MENA-SC 2023
Y2 - 15 November 2023 through 18 November 2023
ER -
