SPECIAL ISSUE PAPER
Economic Analysis for Sustainable Renovation
 
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National Taiwan University of Science and Technology, Department of Architecture, Taipei, TAIWAN
 
 
Online publication date: 2017-11-24
 
 
Publication date: 2017-11-24
 
 
EURASIA J. Math., Sci Tech. Ed 2017;13(12):8139-8147
 
This article belongs to the special issue "Problems of Application Analysis in Knowledge Management and Science-Mathematics-Education".
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ABSTRACT
The volume of existing buildings is much more than new buildings in developed countries. Applying new technology, new material and new equipment to renovate and make the existing buildings greener is crucial for sustainable development. An approach including current energy statistics survey, expert diagnosis, energy and economic simulation using eQUEST model is carried out in this research for an existing office building in Taipei City. A sustainable renovation scheme with a payback period of 5.75 years is proposed in this research. Lessons learned from this research can be further developed into a decision support system to assist existing office building diagnosis and sustainable renovation in a subtropical area.
 
REFERENCES (14)
1.
Brounen, D., Kok, N., & Quigley, J. M. (2012). Residential energy use and conservation: Economics and demographics. European Economic Review, 56(5), 931-945.
 
2.
Bureau of Energy, Ministry of Economic Affairs. (2015). Energy audit annual report for non-productive industries (Chinese Version).
 
3.
Caccavelli, D., & Gugerli, H. (2002). TOBUS — a European diagnosis and decision-making tool for office building upgrading. Energy and Buildings, 34(2), 113-119.
 
4.
Çakmanu, I. (2007). Renovation of existing office buildings in regard to energy economy: An example from Ankara, Turkey. Building and Environment, 42(3), 1348-1357.
 
5.
Cole, R. J. & Kernan, P. C. (1996). Life-cycle energy use in office buildings. Building and Environment, 31(4), 307-317.
 
6.
Egbu, C. O. (1997). Refurbishment management: challenges and opportunities. Building Research and Information, 25(6), 338–347.
 
7.
Hartkopf, V., & Loftness, V. (1999). Global relevance of total building performance. Automation in Construction, 8(4), 377–393.
 
8.
Hsu, Y. H., & Juan, Y. K. (2016). ANN-based decision model for the reuse of vacant buildings in urban areas. International Journal of Strategic Property Management, 20(1), 31-43.
 
9.
Juan Y. K., Peng, G., & Wang, J. (2010). A hybrid decision support system for sustainable office building renovation and energy performance improvement. Energy and Buildings, 42(3), 290-297.
 
10.
Norford, L. K., Socolow, R. H., Hsieh, E. S., & Spadaro, G. V. (1994). Two-to-one discrepancy between measured and predicted performance of a ‘low-energy’ office building: insights from a reconciliation based on the DOE-2 model. Energy and Buildings, 21(2), 121-131.
 
11.
Pérez-Lombard, L., Ortiz, J., & Pout, C. (2008). A review on buildings energy consumption information. Energy and Buildings, 40(3), 394-398.
 
12.
Rey, E. (2004). Office building retrofitting strategies: multicriteria approach of an architectural and technical issue. Energy and Buildings, 36(4), 367-372.
 
13.
Song, J., Zhang, X., & Meng, X. (2015). Simulation and analysis of a university library energy consumption based on eQUEST. Procedia Engineering, 121, 1382-1388.
 
14.
Yohanis, Y. G., & Norton, B. (2002). Life-cycle operational and embodied energy for a generic single-storey office building in the UK. Energy, 27(1), 77-92.
 
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