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

Asfand Y. Khan, Zeshan Ahmad, Tipu Sultan, Saad Alshahrani (), Khazar Hayat and Muhammad Imran
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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

Energies, 2022, vol. 15, issue 24, 1-15

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.

Keywords: genetic algorithm; rooftop solar arrays; optimization; wind pressure; wind design; CFD (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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