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Optimization of Photovoltaic Panel Array Configurations to Reduce Lift Force Using Genetic Algorithm and CFD

Author

Listed:
  • Asfand Y. Khan

    (School of Engineering (SEN), Department of Mechanical Engineering, University of Management & Technology, C II Johar Town, Lahore 54770, Pakistan)

  • Zeshan Ahmad

    (School of Engineering (SEN), Department of Mechanical Engineering, University of Management & Technology, C II Johar Town, Lahore 54770, Pakistan)

  • Tipu Sultan

    (School of Engineering (SEN), Department of Mechanical Engineering, University of Management & Technology, C II Johar Town, Lahore 54770, Pakistan)

  • Saad Alshahrani

    (Department of Mechanical Engineering, College of Engineering, King Khalid University, P.O. Box 394, Abha 61421, Saudi Arabia)

  • Khazar Hayat

    (School of Engineering (SEN), Department of Mechanical Engineering, University of Management & Technology, C II Johar Town, Lahore 54770, Pakistan)

  • Muhammad Imran

    (Department of Mechanical, Biomedical and Design Engineering, College of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK)

Abstract

Aerodynamic lift force acting on the solar structure is important while designing the counterweight for rooftop-mounted solar systems. Due to their unique configuration, the load estimated for solar structures using international building codes can be either higher or lower than the actual. Computational Fluid Dynamics(CFD) simulations haveproven to be an efficient tool for estimating wind loads on solar panels for design purposes and identifying critical design cases. Computational Fluid Dynamics (CFD) simulations usually require high computation power, and slight changes in geometry to find optimum configuration can be time-consuming. An optimization method to minimize lift force effects on solar photovoltaic (PV) arrays installed on rooftops usesthe Computational Fluid Dynamics (CFD)and genetic algorithms proposed in this paper. The tilt angle and pitch between two rows of solar panels were parameterized, and a genetic algorithm was used to search for aconfiguration resulting in minimum wind lift force acting on the solar photovoltaic plant. Only combinations with a performance ratio >80% were considered. Three different rooftopphotovoltaic (PV) plant layout configurations were analyzed in this research. Two rows of photovoltaic (PV) panel arrays wereconsidered for optimization in the 2D domain using ANSYS Fluent. Results showed that the difference in wind-liftforce between optimized configurations against that with maximum lift force configuration for all three cases above was fifty percent.

Suggested Citation

  • Asfand Y. Khan & Zeshan Ahmad & Tipu Sultan & Saad Alshahrani & Khazar Hayat & Muhammad Imran, 2022. "Optimization of Photovoltaic Panel Array Configurations to Reduce Lift Force Using Genetic Algorithm and CFD," Energies, MDPI, vol. 15(24), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9580-:d:1006308
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    References listed on IDEAS

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    1. Timmidi Nagadurga & Pasumarthi Venkata Ramana Lakshmi Narasimham & V. S. Vakula & Ramesh Devarapalli & Fausto Pedro García Márquez, 2021. "Enhancing Global Maximum Power Point of Solar Photovoltaic Strings under Partial Shading Conditions Using Chimp Optimization Algorithm," Energies, MDPI, vol. 14(14), pages 1-23, July.
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    Cited by:

    1. Murilo Eduardo Casteroba Bento, 2023. "Wide-Area Measurement-Based Two-Level Control Design to Tolerate Permanent Communication Failures," Energies, MDPI, vol. 16(15), pages 1-15, July.

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