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Comparing View Factor modeling frameworks for the estimation of incident solar energy

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  • Arias-Rosales, Andrés
  • LeDuc, Philip R.

Abstract

View Factors are instrumental in using widely available horizontal solar radiation data for calculating the incident radiation on harvesting surfaces with arbitrary positions. This capability is notably useful for the design, optimization, and performance forecasting of solar devices. There are several main View Factor models (Liu-Jordan’s, Tian’s, and Badescu’s), which can lead to different theoretical implications and energy estimates. However, the assessments about the validity and underlying assumptions of these models are sometimes contradictory. Resolving this is important for utilizing the most appropriate framework given specific schemes and modeling goals. This work presents a comparative systematic analysis of a wide range of View Factor modeling frameworks with the purpose to gain a deeper understanding of the theoretical consistency and implications of the main View Factor models. The different sets of assumptions are evaluated through stochastic rays simulations and verified against integral models. Five frameworks for the Isotropic and Albedo View Factors were found to be consistent with Liu-Jordan’s model, two with Tian’s, and two with Badescu’s (partially); all with RMSE ⩽0.0014. Considering the most common ways to conceptualize the other components of the radiation, there was consistency with the Perez sky models (RMSE ⩽0.0055) for the View Factor of the Circumsolar radiation as a 25° cone and Horizon Brightening as a flat ring. For the View Factor of the Horizon Brightening as a 6.5° band, two regression models are introduced. By enabling a deeper insight into the sets of assumptions that are consistent with the main View Factor models, this work is valuable for the convergence and best implementation of the various theories in the modeling of incident solar radiation.

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  • Arias-Rosales, Andrés & LeDuc, Philip R., 2020. "Comparing View Factor modeling frameworks for the estimation of incident solar energy," Applied Energy, Elsevier, vol. 277(C).
  • Handle: RePEc:eee:appene:v:277:y:2020:i:c:s0306261920310229
    DOI: 10.1016/j.apenergy.2020.115510
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    References listed on IDEAS

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    1. Badescu, V., 2002. "3D isotropic approximation for solar diffuse irradiance on tilted surfaces," Renewable Energy, Elsevier, vol. 26(2), pages 221-233.
    2. Freitas, S. & Catita, C. & Redweik, P. & Brito, M.C., 2015. "Modelling solar potential in the urban environment: State-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 915-931.
    3. Sengupta, Manajit & Xie, Yu & Lopez, Anthony & Habte, Aron & Maclaurin, Galen & Shelby, James, 2018. "The National Solar Radiation Data Base (NSRDB)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 51-60.
    4. Rakovec, Jože & Zakšek, Klemen, 2012. "On the proper analytical expression for the sky-view factor and the diffuse irradiation of a slope for an isotropic sky," Renewable Energy, Elsevier, vol. 37(1), pages 440-444.
    5. Lingfors, D. & Bright, J.M. & Engerer, N.A. & Ahlberg, J. & Killinger, S. & Widén, J., 2017. "Comparing the capability of low- and high-resolution LiDAR data with application to solar resource assessment, roof type classification and shading analysis," Applied Energy, Elsevier, vol. 205(C), pages 1216-1230.
    6. Ramírez-Faz, J. & López-Luque, R. & Casares, F.J., 2015. "Development of synthetic hemispheric projections suitable for assessing the sky view factor on vertical planes," Renewable Energy, Elsevier, vol. 74(C), pages 279-286.
    7. Gu, Wenbo & Ma, Tao & Li, Meng & Shen, Lu & Zhang, Yijie, 2020. "A coupled optical-electrical-thermal model of the bifacial photovoltaic module," Applied Energy, Elsevier, vol. 258(C).
    8. Arias-Rosales, Andrés & LeDuc, Philip R., 2020. "Modeling the transmittance of anisotropic diffuse radiation towards estimating energy losses in solar panel coverings," Applied Energy, Elsevier, vol. 268(C).
    9. d'Alessandro, Vincenzo & Di Napoli, Fabio & Guerriero, Pierluigi & Daliento, Santolo, 2015. "An automated high-granularity tool for a fast evaluation of the yield of PV plants accounting for shading effects," Renewable Energy, Elsevier, vol. 83(C), pages 294-304.
    10. Yadav, Somil & Panda, S.K. & Hachem-Vermette, Caroline, 2020. "Method to improve performance of building integrated photovoltaic thermal system having optimum tilt and facing directions," Applied Energy, Elsevier, vol. 266(C).
    11. Mohajeri, N. & Gudmundsson, A. & Kunckler, T. & Upadhyay, G. & Assouline, D. & Kämpf, J.H & Scartezzini, J.L., 2019. "A solar-based sustainable urban design: The effects of city-scale street-canyon geometry on solar access in Geneva, Switzerland," Applied Energy, Elsevier, vol. 240(C), pages 173-190.
    12. Chang, Soowon & Saha, Nirvik & Castro-Lacouture, Daniel & Yang, Perry Pei-Ju, 2019. "Multivariate relationships between campus design parameters and energy performance using reinforcement learning and parametric modeling," Applied Energy, Elsevier, vol. 249(C), pages 253-264.
    13. Li, Danny H.W. & Cheung, Gary H.W., 2005. "Study of models for predicting the diffuse irradiance on inclined surfaces," Applied Energy, Elsevier, vol. 81(2), pages 170-186, June.
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    1. Joseph Appelbaum & Avi Aronescu, 2022. "View Factors of Flat Collectors, Including Photovoltaics, Visible to Partial Sky," Energies, MDPI, vol. 15(22), pages 1-17, November.
    2. Saeed Swaid & Joseph Appelbaum & Avi Aronescu, 2021. "Shading and Masking of PV Collectors on Horizontal and Sloped Planes Facing South and North—A Comparative Study," Energies, MDPI, vol. 14(13), pages 1-15, June.
    3. Zainali, Sebastian & Ma Lu, Silvia & Stridh, Bengt & Avelin, Anders & Amaducci, Stefano & Colauzzi, Michele & Campana, Pietro Elia, 2023. "Direct and diffuse shading factors modelling for the most representative agrivoltaic system layouts," Applied Energy, Elsevier, vol. 339(C).
    4. Arias-Rosales, Andrés & LeDuc, Philip R., 2023. "Urban solar harvesting: The importance of diffuse shadows in complex environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    5. Aronescu, A. & Appelbaum, J., 2024. "Sky view factors of curved surfaces," Renewable Energy, Elsevier, vol. 224(C).
    6. Arias-Rosales, Andrés & LeDuc, Philip R., 2022. "Shadow modeling in urban environments for solar harvesting devices with freely defined positions and orientations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).

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