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Energy optimization of building design for different housing units in apartment buildings


  • Yao, Jian


Current energy designs for a building in China focus on the energy efficiency of the whole building and thus often neglect the energy difference between different housing units in apartment buildings. The best design technique in terms of energy savings is not only to decrease whole building energy demand, but also to reduce the energy difference between different housing units to a relatively low level. This paper introduces an important index “energy performance difference between housing units” (EDH) to evaluate the drawbacks of conventional designs on a typical residential building in hot summer and cold winter zone. Then nine improved design options were considered as the possible strategies to diminish the EDH, based on a number of building simulations with the program DeST-h. Results show that the option 9 (add movable shading for the east facing windows and west facing windows, and reduce the U-values of the east walls and west facing windows), an improved design strategy according to the EDH of the current design, reduces the EDH to less than 4% that is much lower than other options and meanwhile ensures a decrease in whole building energy demands. A case study was carried out to validate the effectiveness of this index in optimization. As a conclusion, EDH is a very useful index for optimizing energy designs of apartment buildings and can be used in China to improve conventional building designs.

Suggested Citation

  • Yao, Jian, 2012. "Energy optimization of building design for different housing units in apartment buildings," Applied Energy, Elsevier, vol. 94(C), pages 330-337.
  • Handle: RePEc:eee:appene:v:94:y:2012:i:c:p:330-337
    DOI: 10.1016/j.apenergy.2012.02.006

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    References listed on IDEAS

    1. Yu, Jinghua & Yang, Changzhi & Tian, Liwei & Liao, Dan, 2009. "Evaluation on energy and thermal performance for residential envelopes in hot summer and cold winter zone of China," Applied Energy, Elsevier, vol. 86(10), pages 1970-1985, October.
    2. Yu, Jinghua & Yang, Changzhi & Tian, Liwei & Liao, Dan, 2009. "A study on optimum insulation thicknesses of external walls in hot summer and cold winter zone of China," Applied Energy, Elsevier, vol. 86(11), pages 2520-2529, November.
    3. Bartusch, Cajsa & Odlare, Monica & Wallin, Fredrik & Wester, Lars, 2012. "Exploring variance in residential electricity consumption: Household features and building properties," Applied Energy, Elsevier, vol. 92(C), pages 637-643.
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    Cited by:

    1. Ye, Hong & Meng, Xianchun & Long, Linshuang & Xu, Bin, 2013. "The route to a perfect window," Renewable Energy, Elsevier, vol. 55(C), pages 448-455.
    2. Piechocki, Janusz & Ambroziak, Dominik & Palkowski, Aleksander & Redlarski, Grzegorz, 2014. "Use of Modified Cuckoo Search algorithm in the design process of integrated power systems for modern and energy self-sufficient farms," Applied Energy, Elsevier, vol. 114(C), pages 901-908.
    3. Karmellos, M. & Kiprakis, A. & Mavrotas, G., 2015. "A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies," Applied Energy, Elsevier, vol. 139(C), pages 131-150.
    4. Fabrizio Ascione & Nicola Bianco & Rosa Francesca De Masi & Gerardo Maria Mauro & Giuseppe Peter Vanoli, 2015. "Design of the Building Envelope: A Novel Multi-Objective Approach for the Optimization of Energy Performance and Thermal Comfort," Sustainability, MDPI, Open Access Journal, vol. 7(8), pages 1-28, August.
    5. Jian Yao, 2014. "A Multi-Objective (Energy, Economic and Environmental Performance) Life Cycle Analysis for Better Building Design," Sustainability, MDPI, Open Access Journal, vol. 6(2), pages 1-13, January.
    6. Rodrigues, Eugénio & Gaspar, Adélio Rodrigues & Gomes, Álvaro, 2014. "Improving thermal performance of automatically generated floor plans using a geometric variable sequential optimization procedure," Applied Energy, Elsevier, vol. 132(C), pages 200-215.
    7. Gang, Wenjie & Wang, Jinbo, 2013. "Predictive ANN models of ground heat exchanger for the control of hybrid ground source heat pump systems," Applied Energy, Elsevier, vol. 112(C), pages 1146-1153.
    8. Cristina Carletti & Fabio Sciurpi & Leone Pierangioli, 2014. "The Energy Upgrading of Existing Buildings: Window and Shading Device Typologies for Energy Efficiency Refurbishment," Sustainability, MDPI, Open Access Journal, vol. 6(8), pages 1-24, August.
    9. De Boeck, L. & Verbeke, S. & Audenaert, A. & De Mesmaeker, L., 2015. "Improving the energy performance of residential buildings: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 960-975.
    10. Clune, Stephen & Morrissey, John & Moore, Trivess, 2012. "Size matters: House size and thermal efficiency as policy strategies to reduce net emissions of new developments," Energy Policy, Elsevier, vol. 48(C), pages 657-667.
    11. Best, Robert E. & Flager, Forest & Lepech, Michael D., 2015. "Modeling and optimization of building mix and energy supply technology for urban districts," Applied Energy, Elsevier, vol. 159(C), pages 161-177.
    12. Won-Jun Suh & Cheol-Soo Park, 2017. "Heuristic vs . Meta-Heuristic Optimal Energy Design for an Office Building," Sustainability, MDPI, Open Access Journal, vol. 9(4), pages 1-15, March.


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