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Developing a fuzzy analytic hierarchical process model for building energy conservation assessment

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  • Zheng, Guozhong
  • Jing, Youyin
  • Huang, Hongxia
  • Shi, Guohua
  • Zhang, Xutao

Abstract

The building sector is responsible for one-third of global final energy consumption. The object of building conservation assessment is to establish and limit the upper boundary for energy consumption in buildings and to promote the utilization of renewable energy and new energy technologies and products. In this paper, a methodology based on fuzzy analytic hierarchy process (FAHP) is proposed for building energy conservation assessment. Within the proposed model, seven factors (building structure, wall, roof, door and window, heating and air conditioning, equipment, and energy) and 22 sub-factors are defined. In the assessment, a decision group is established and members in the decision group are required to provide linguistic variables on the basis of their knowledge and expertise for each sub-factor at the bottom level. Then the decision group is asked to compare the elements at a given level on a pair-wise basis by triangular fuzzy number, then fuzzy pair-wise comparison matrixes are constructed to determine the weights of the factors and sub-factors. The membership degrees on each sub-factor and factor are calculated based on the assessment results. The fuzzy synthesis assessment matrix and the fuzzy synthesis assessment result are then calculated. In order to distinguish the energy conservation degree, the building energy conservation star system is established and the building energy conservation star of the building is obtained according to the assessment results. Then an example is used to illustrate the proposed approach. The results demonstrate the engineering practicability and effectiveness of this method.

Suggested Citation

  • Zheng, Guozhong & Jing, Youyin & Huang, Hongxia & Shi, Guohua & Zhang, Xutao, 2010. "Developing a fuzzy analytic hierarchical process model for building energy conservation assessment," Renewable Energy, Elsevier, vol. 35(1), pages 78-87.
  • Handle: RePEc:eee:renene:v:35:y:2010:i:1:p:78-87
    DOI: 10.1016/j.renene.2009.07.008
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    References listed on IDEAS

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    1. Xia, Chunhai & Zhu, Yingxin & Lin, Borong, 2008. "Renewable energy utilization evaluation method in green buildings," Renewable Energy, Elsevier, vol. 33(5), pages 883-886.
    2. Kahraman, Cengiz & Ertay, Tijen & Buyukozkan, Gulcin, 2006. "A fuzzy optimization model for QFD planning process using analytic network approach," European Journal of Operational Research, Elsevier, vol. 171(2), pages 390-411, June.
    3. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    4. Tolga, Ethem & Demircan, Murat Levent & Kahraman, Cengiz, 2005. "Operating system selection using fuzzy replacement analysis and analytic hierarchy process," International Journal of Production Economics, Elsevier, vol. 97(1), pages 89-117, July.
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    2. Doukas, Haris, 2013. "Modelling of linguistic variables in multicriteria energy policy support," European Journal of Operational Research, Elsevier, vol. 227(2), pages 227-238.
    3. Weeks, Kelly & Safa, Mahdi & Kenyon, George & Levius, Seon, 2020. "Offshore multi-purpose platform efficacy by U.S. coastal areas," Renewable Energy, Elsevier, vol. 152(C), pages 1451-1464.

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