Simulation of dynamic response of a ground-mounted solar panel array under stochastic wind loading

This paper presents a novel simulation framework for estimating the dynamic response of a ground-mounted solar panel array under stationary wind loads which are spatially correlated across the length of the solar panel array.Specifically, the framework uses mean pressure coefficient distributions derived using the computational fluid dynamics (CFD) simulation software WE-UQ.Note that for the CFD simulation, the input wind field across the length of the solar panel array was uniform.The accuracy of the CFD simulation is validated by comparing the simulated mean pressure coefficients with those derived from wind tunnel tests.Next, simulated stochastic wind loads are generated from the stationary wind speed using a stochastic wave approach from the spectral representation method (SRM), as well as the mean pressure coefficients derived from the CFD simulation.Further, the simulated wind loads are applied to a solar panel array finite element model using the finite element software OpenSees to simulate dynamic response.Torsional strains on the torque tube are estimated to observe the performance of the solar panel array.The torsional strains obtained from the proposed wind generation method are compared with simulation results that use wind tunnel test data to define the loading; the proposed method generates significantly larger dynamic excitations, especially in higher vibration modes.This is primarily attributed to the spatially varying, but correlated, wind speeds.Consequently, the proposed simulation framework provides a valuable novel tool for solar panel array analysis.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.23967/icossar.2025.040
Primary Topic
Wind and Air Flow Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Simulation of dynamic response of a ground-mounted solar panel array under stochastic wind loading

Yan Li, M. DeJong, H. Zhang
Wind and Air Flow Studies
article

Simulation of dynamic response of a ground-mounted solar panel array under stochastic wind loading

Yan Li, M. DeJong, H. Zhang
article en

Abstract

This paper presents a novel simulation framework for estimating the dynamic response of a ground-mounted solar panel array under stationary wind loads which are spatially correlated across the length of the solar panel array.Specifically, the framework uses mean pressure coefficient distributions derived using the computational fluid dynamics (CFD) simulation software WE-UQ.Note that for the CFD simulation, the input wind field across the length of the solar panel array was uniform.The accuracy of the CFD simulation is validated by comparing the simulated mean pressure coefficients with those derived from wind tunnel tests.Next, simulated stochastic wind loads are generated from the stationary wind speed using a stochastic wave approach from the spectral representation method (SRM), as well as the mean pressure coefficients derived from the CFD simulation.Further, the simulated wind loads are applied to a solar panel array finite element model using the finite element software OpenSees to simulate dynamic response.Torsional strains on the torque tube are estimated to observe the performance of the solar panel array.The torsional strains obtained from the proposed wind generation method are compared with simulation results that use wind tunnel test data to define the loading; the proposed method generates significantly larger dynamic excitations, especially in higher vibration modes.This is primarily attributed to the spatially varying, but correlated, wind speeds.Consequently, the proposed simulation framework provides a valuable novel tool for solar panel array analysis.

U.S. Department of Energy, Center of Excellence in Applied Computational Science and Engineering, Solar Energy Technologies Office
Affordable and clean energy
Openalex Percentile: Top 87%
Wind and Air Flow Studies
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Simulation of dynamic response of a ground-mounted solar panel array under stochastic wind loading — Yan Li, M. DeJong, et al. · (2025) | TGRS Research Map | TGRS