IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v7y2014i11p6897-6929d41776.html
   My bibliography  Save this article

A Heuristic Rule-Based Passive Design Decision Model for Reducing Heating Energy Consumption of Korean Apartment Buildings

Author

Listed:
  • Dongjun Suh

    (KAIST Institute for Information Technology Convergence, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 305-701, Korea)

  • Seongju Chang

    (Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 305-701, Korea)

Abstract

This research presents an evaluative energy model for estimating the energy efficiency of the design choices of architects and engineers in the early design phase. We analyze the effects of various parameters with different characteristics in various combinations for building energy consumption. With this analysis, we build a database that identifies a set of heuristic rules for energy-efficient building design to facilitate the design of sustainable apartment housing. Perturbation studies are based on a sensitivity analysis used to identify the thermal influence of the input design parameters on various simulation outputs and compare the results to a reference case. Energy sensitivity weight factors are obtained from an extensive sensitivity study using building energy simulations. The results of the energy sensitivity study summarized in a set of heuristic rules for evaluating architectural features are estimated through case studies of Korean apartment buildings. This study offers valuable guidelines for developing energy-efficient residential housing in Korea and will help architects in considering appropriate design schemes and provide a ready reference to generalized test cases for both architects and engineers so that they can zero in on a set of effective design solutions.

Suggested Citation

  • Dongjun Suh & Seongju Chang, 2014. "A Heuristic Rule-Based Passive Design Decision Model for Reducing Heating Energy Consumption of Korean Apartment Buildings," Energies, MDPI, vol. 7(11), pages 1-33, October.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:11:p:6897-6929:d:41776
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/7/11/6897/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/7/11/6897/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dongjun Suh & Seongju Chang, 2012. "An Energy and Water Resource Demand Estimation Model for Multi-Family Housing Complexes in Korea," Energies, MDPI, vol. 5(11), pages 1-20, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vivian W. Y. Tam & Khoa N. Le & J. Y. Wang, 2018. "Cost Implication of Implementing External Facade Systems for Commercial Buildings," Sustainability, MDPI, vol. 10(6), pages 1-22, June.
    2. Mansu Kim & Sungwon Jung & Joo-won Kang, 2019. "Artificial Neural Network-Based Residential Energy Consumption Prediction Models Considering Residential Building Information and User Features in South Korea," Sustainability, MDPI, vol. 12(1), pages 1-28, December.
    3. Cristina Brunelli & Francesco Castellani & Alberto Garinei & Lorenzo Biondi & Marcello Marconi, 2016. "A Procedure to Perform Multi-Objective Optimization for Sustainable Design of Buildings," Energies, MDPI, vol. 9(11), pages 1-15, November.
    4. Byeongjoon Noh & Juntae Son & Hansaem Park & Seongju Chang, 2017. "In-Depth Analysis of Energy Efficiency Related Factors in Commercial Buildings Using Data Cube and Association Rule Mining," Sustainability, MDPI, vol. 9(11), pages 1-20, November.

    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. Seo, Dong-yeon & Koo, Choongwan & Hong, Taehoon, 2015. "A Lagrangian finite element model for estimating the heating and cooling demand of a residential building with a different envelope design," Applied Energy, Elsevier, vol. 142(C), pages 66-79.
    2. Chi Zhang & Zhengning Pu & Jiasha Fu, 2018. "The Recurrence Interval Difference of Power Load in Heavy/Light Industries of China," Energies, MDPI, vol. 11(1), pages 1-20, January.
    3. Wai-Ming To & Peter Ka Chun Lee & Tsz-Ming Lai, 2017. "Modeling of Monthly Residential and Commercial Electricity Consumption Using Nonlinear Seasonal Models—The Case of Hong Kong," Energies, MDPI, vol. 10(7), pages 1-16, June.
    4. Koo, Choongwan & Park, Sungki & Hong, Taehoon & Park, Hyo Seon, 2014. "An estimation model for the heating and cooling demand of a residential building with a different envelope design using the finite element method," Applied Energy, Elsevier, vol. 115(C), pages 205-215.
    5. Oh, Jeongyoon & Koo, Choongwan & Hong, Taehoon & Cha, Seung Hyun, 2018. "An integrated model for estimating the techno-economic performance of the distributed solar generation system on building façades: Focused on energy demand and supply," Applied Energy, Elsevier, vol. 228(C), pages 1071-1090.
    6. Lucheng Hong & Wantao Shu & Angela C. Chao, 2018. "Recurrence Interval Analysis on Electricity Consumption of an Office Building in China," Sustainability, MDPI, vol. 10(2), pages 1-15, January.

    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:7:y:2014:i:11:p:6897-6929:d:41776. 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.