IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v82y2005i4p313-330.html
   My bibliography  Save this article

Effect of electricity tariff on the optimum insulation-thickness in building walls as determined by a dynamic heat-transfer model

Author

Listed:
  • Al-Sanea, Sami A.
  • Zedan, M.F.
  • Al-Ajlan, Saleh A.

Abstract

Thermal insulation is one of the most effective energy-conservation measures in buildings. Despite the widespread use of insulation materials in recent years, little is known regarding their optimum thickness under dynamic thermal conditions. Insulated concrete blocks are among the units most commonly used in the construction of building walls in Saudi Arabia. Typically, the insulation layer thickness is fixed at a value in the range 2.5-7.5Â cm, regardless of the climatic conditions, type and cost of insulation material, and other economic parameters. In the present study, a numerical model based on a finite-volume, time-dependent implicit procedure, which has been previously validated, is used to compute the yearly cooling and heating transmission loads under steady periodic conditions through a typical building wall, for different insulation thicknesses. The transmission loads, calculated by using the climatic conditions of Riyadh for a west-facing wall, are fed into an economic model in order to determine the optimum thickness of insulation (Lopt). The latter corresponds to the minimum total cost, which includes the cost of insulation material and its installation plus the present value of energy consumption cost over the lifetime of the building. The optimum insulation thickness depends on the electricity tariff as well as the cost of insulation material, lifetime of the building, inflation and discount rates, and coefficient of performance of the air-conditioning equipment. In the present study, the effect of electricity tariff on the computed optimum insulation thickness is investigated. Different average electricity tariffs are considered; namely, 0.05, 0.1, 0.2, 0.3 and 0.4 SR/kWh (designated as Cases 1-5, respectively; 1 US$Â =Â 3.75 Saudi Riyals). Results using moulded polystyrene as an insulating material show that the values of Lopt are: 4.8, 7.2, 10.9, 13.7 and 16.0Â cm for Cases 1-5. Under the conditions of optimal insulation thickness for each electricity tariff, Case 1 gives the lowest total cost of 17.4 SR/m2, while Case 5 gives the highest total cost of 53.1 SR/m2. Corresponding thermal performance characteristics in terms of yearly total and peak transmission loads, R-value, time lag and decrement factor are presented.

Suggested Citation

  • Al-Sanea, Sami A. & Zedan, M.F. & Al-Ajlan, Saleh A., 2005. "Effect of electricity tariff on the optimum insulation-thickness in building walls as determined by a dynamic heat-transfer model," Applied Energy, Elsevier, vol. 82(4), pages 313-330, December.
    • Handle: RePEc:eee:appene:v:82:y:2005:i:4:p:313-330
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306-2619(04)00196-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Al-Sanea, Sami A. & Zedan, M. F. & Al-Ajlan, Saleh A., 2004. "Adjustment factors for the ASHRAE clear-sky model based on solar-radiation measurements in Riyadh," Applied Energy, Elsevier, vol. 79(2), pages 215-237, October.
    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. Al-Sanea, Sami A. & Zedan, M.F., 2011. "Improving thermal performance of building walls by optimizing insulation layer distribution and thickness for same thermal mass," Applied Energy, Elsevier, vol. 88(9), pages 3113-3124.
    2. Das, Aparna & Paul, Saikat Kumar, 2015. "Artificial illumination during daytime in residential buildings: Factors, energy implications and future predictions," Applied Energy, Elsevier, vol. 158(C), pages 65-85.
    3. Daouas, Naouel, 2016. "Impact of external longwave radiation on optimum insulation thickness in Tunisian building roofs based on a dynamic analytical model," Applied Energy, Elsevier, vol. 177(C), pages 136-148.
    4. Al-Sanea, Sami A. & Zedan, M.F., 2008. "Optimized monthly-fixed thermostat-setting scheme for maximum energy-savings and thermal comfort in air-conditioned spaces," Applied Energy, Elsevier, vol. 85(5), pages 326-346, May.
    5. Hepbasli, Arif & Alsuhaibani, Zeyad, 2011. "A key review on present status and future directions of solar energy studies and applications in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 5021-5050.
    6. Wu, Yujie & Wang, Jianzhou, 2016. "A novel hybrid model based on artificial neural networks for solar radiation prediction," Renewable Energy, Elsevier, vol. 89(C), pages 268-284.
    7. Qiusheng Wang & Jianping Xian & Jun Xiao & Shuai Zou, 2023. "Simulation Study on Sunshine Temperature Field of a Concrete Box Girder of the Cable-Stayed Bridge," Sustainability, MDPI, vol. 15(9), pages 1-28, May.
    8. El Ouderni, Ahmed Ridha & Maatallah, Taher & El Alimi, Souheil & Ben Nassrallah, Sassi, 2013. "Experimental assessment of the solar energy potential in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 155-168.
    9. Al-Sanea, Sami A. & Zedan, M.F. & Al-Hussain, S.N., 2013. "Effect of masonry material and surface absorptivity on critical thermal mass in insulated building walls," Applied Energy, Elsevier, vol. 102(C), pages 1063-1070.
    10. Al-Sanea, Sami A. & Zedan, M.F., 2012. "Effect of thermal bridges on transmission loads and thermal resistance of building walls under dynamic conditions," Applied Energy, Elsevier, vol. 98(C), pages 584-593.

    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:eee:appene:v:82:y:2005:i:4:p:313-330. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.