IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i20p3826-d274865.html
   My bibliography  Save this article

Radiation View Factor for Building Applications: Comparison of Computation Environments

Author

Listed:
  • Marzia Alam

    (School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Boundary Rd N, Edinburgh EH14 4AS, UK)

  • Mehreen Saleem Gul

    (School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Boundary Rd N, Edinburgh EH14 4AS, UK)

  • Tariq Muneer

    (School of Engineering and The Built Environment, Edinburgh Napier University, 10 Colinton Rd, Edinburgh EH10 5DT, UK)

Abstract

Computation of view factors is required in several building engineering applications where radiative exchange takes place between surfaces such as ground and vertical walls or ground and sloping thermal or photovoltaics collectors. In this paper, view factor computations are performed for bifacial solar photovoltaic (PV) collectors based on the finite element method (FEM) using two programming languages known as Microsoft Excel-Visual Basic for Applications (VBA) and Python. The aim is to determine the computer response time as well as the performance of the two languages in terms of accuracy and convergence of the numerical solution. To run the simulations in Python, an open source just-in-time (JIT) compiler called Numba was used and the same program was also run as a macro in VBA. It was observed that the simulation response time significantly decreased in Python when compared to VBA. This decrease in time was due to the increase in the total number of iterations from 400 million to 250 billion for a given case. Results demonstrated that Python was 71–180 times faster than VBA and, therefore, offers a better programming platform for the view factor analysis and modelling of bifacial solar PV where computation time is a significant modelling challenge.

Suggested Citation

  • Marzia Alam & Mehreen Saleem Gul & Tariq Muneer, 2019. "Radiation View Factor for Building Applications: Comparison of Computation Environments," Energies, MDPI, vol. 12(20), pages 1-14, October.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3826-:d:274865
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/20/3826/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/20/3826/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. Ahmadi & P. H. Robinson & F. Elizondo & P. Chilibroste, 2018. "Implementation of CTR Dairy Model Using the Visual Basic for Application Language of Microsoft Excel," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 9(3), pages 74-86, July.
    2. Carlos Rubio-Bellido & Jesús A. Pulido-Arcas & Benito Sánchez-Montañés, 2015. "A Simplified Simulation Model for Predicting Radiative Transfer in Long Street Canyons under High Solar Radiation Conditions," Energies, MDPI, vol. 8(12), pages 1-19, December.
    3. Marius Zoder & Janosch Balke & Mathias Hofmann & George Tsatsaronis, 2018. "Simulation and Exergy Analysis of Energy Conversion Processes Using a Free and Open-Source Framework—Python-Based Object-Oriented Programming for Gas- and Steam Turbine Cycles," Energies, MDPI, vol. 11(10), pages 1-19, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daissy Lorena Restrepo-Serna & Jimmy Anderson Martínez-Ruano & Carlos Ariel Cardona-Alzate, 2018. "Energy Efficiency of Biorefinery Schemes Using Sugarcane Bagasse as Raw Material," Energies, MDPI, vol. 11(12), pages 1-12, December.
    2. Elena Garcia-Nevado & Anna Pages-Ramon & Helena Coch, 2016. "Solar Access Assessment in Dense Urban Environments: The Effect of Intersections in an Urban Canyon," Energies, MDPI, vol. 9(10), pages 1-12, October.
    3. Francesco Witte & Mathias Hofmann & Julius Meier & Ilja Tuschy & George Tsatsaronis, 2022. "Generic and Open-Source Exergy Analysis—Extending the Simulation Framework TESPy," Energies, MDPI, vol. 15(11), pages 1-27, June.
    4. Alessandra Curreli & Glòria Serra-Coch & Antonio Isalgue & Isabel Crespo & Helena Coch, 2016. "Solar Energy as a Form Giver for Future Cities," Energies, MDPI, vol. 9(7), pages 1-11, July.
    5. Flórez-Orrego, Daniel & Albuquerque, Cyro & da Silva, Julio A.M. & Freire, Ronaldo Lucas Alkmin & de Oliveira Junior, Silvio, 2021. "Optimal design of power hubs for offshore petroleum platforms," Energy, Elsevier, vol. 235(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3826-:d:274865. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.