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Analyzing Energy Reduction Correlations among Factors of Building Energy Retrofit by using BEAT Program

BEAT 프로그램을 이용한 건물에너지 retrofit 요소들 간의 에너지 절감 관계분석

  • Received : 2016.10.12
  • Accepted : 2016.12.30
  • Published : 2017.02.28

Abstract

Recently, Korean government is successively driving energy saving policies. Nevertheless, the use of energy is continuously increasing, and shift toward a low-energy society is somewhat out of our expectation. The major goal of building energy retrofit is to optimize energy consumption in existing buildings which are under deterioration. Many of these old buildings with lower efficiency spend more energy than newly built ones. Thus, this paper suggests a reasonable guideline for energy retrofit. A government office building located in Kangdonggu, Seoul is selected as the subject building, and a modified bin-method called BEAT(Building Energy Analysis Tool) program is used for the analysis. The primary goal of this research is to find the best combination of influencing factors that can improve energy efficiency in old buildings. Such factors stem from design components of Building, System and also Operational facets of a building. By applying the input standards from 'Green remodeling guidelines', heating energy can be reduced by 38.28% in the winter and 38.50% of cooling energy in the summer. Most of the factors contributed to reducing energy consumption except for SC(Shading Coefficient) and Internal lighting to heating energy. This is due to the blockage of solar heat gain and decrement of internal heat respectively, which results in a higher demand for heating in the winter. Finally, the total energy(HVAC+Lighting+Office equipment) on a yearly basis, can be reduced by 38.89% when all the considering factors are applied in combination. The study will further move to analyze the best solution for building energy retrofit.

Keywords

Acknowledgement

Supported by : 한국에너지기술평가원(KETEP)

References

  1. Park, H. J., Kim, S. H., Cho, S., & Yee, J. J. (2010). Estimation of Energy Performance for the Integrated Module of Energy Saving Element Technology by TRNSYS in Office Building, proceedings of Korean Institute of Architectural Sustainable Environment and Building Systems, 2010.10, 153-156.
  2. Kim, G. S., & Leigh. S. B. (2015). Quantitative Simulation Models Developments for Building Retrofit Promotion, proceedings of The Society of Air-Conditioning and Refrigerating Engineers of Korea, Space, 45(33), 22.
  3. Kim, Y, K., & Lee, T. W. (2012). An Analysis of the Energy Saving Effect Through the Retrofit and the Optimal Operation for HVAC Systems, Korean Journal of Air-Conditioning and Refrigeration Engineering, 24(4), 343-350. https://doi.org/10.6110/KJACR.2012.24.4.343
  4. Woo, H. J., Choi, K. W., Kim, H. S., & et al. (2016). A Study on Classifying Building Energy Consumption Pattern Using Actual Building Energy Data, Journal of the Archi- tectural Institute of Korea Planning & Design 32(5), 2016.5, 143-151. https://doi.org/10.5659/JAIK_PD.2016.32.5.143
  5. Krarti, M. (2009). Energy audit of building systems, CRC Press, 2009.
  6. Kang, K. M. (2015). Application of BEAT(Building Energy Analysis Tool) for non residential building energy analysis (Master's thesis), Yonsei University, Seoul, Republic or Korea. 2015.
  7. Tzempelikos, A., & Athienitis, A. K. (2007). The impact of shading design and control on building cooling and lighting demand, Solar Energy, 81(3), 369-382. https://doi.org/10.1016/j.solener.2006.06.015
  8. Sozer, H. (2010). Improving energy efficiency through the design of the building envelope, Building and environment, 45(12), 2581-2593. https://doi.org/10.1016/j.buildenv.2010.05.004
  9. Heo, Y., Choudhary, R., & Augenbroe, G. A. (2012). Calibration of building energy models for retrofit analysis under uncertainty, Energy and Buildings, 47, 550-560. https://doi.org/10.1016/j.enbuild.2011.12.029
  10. Kim, K. H., & Haberl, J. S. (2015). Development of methodology for calibrated simulation in single-family residential buildings using three-parameter change-point regression model, Energy and Buildings, 99, 140-152. https://doi.org/10.1016/j.enbuild.2015.04.032
  11. Jang, C. Y., Han, H. S., & Lee, J. S. (2010). The Building Energy Efficiency Rating Evaluation of Apartment depending on SC and Window area ratio, Journal of the Korean Solar Energy Society, 30(5).
  12. Cheong, C. H., Kim, T. H., & Leigh, S. B. (2010). Heating Load Reduction by Energy Retrofit in an Old Residential Building, Journal of the Architectural Institute of Korea Planning & Design 26(7), 2010, 275-282.
  13. Cho, Y. H., Baek, S. H., & Kim, K. W. (2010). Study on the Building Energy Audit through Field Measurement, Journal of the Korean Society of Living Environmental System 27(6).
  14. Liu, G., & Liu, M. (2011). A rapid calibration procedure and case study for simplified simulation models of com- monly used HVAC systems, Building and Environment, 46(2), 409-420. https://doi.org/10.1016/j.buildenv.2010.08.002
  15. Haberl, J. S., & Thamilseran, S. (1994). A bin method for calculating energy conservation retrofit savings in commercial buildings.
  16. Lee, M. J., Kim, W. S., Lee, W. J., & Lee, W. T. (2012). A Study about Reduction Rates of Building Energy Demand for a Detached House according to Building Energy Efficient Methods, Journal of the Architectural Institute of Korea Planning & Design 28(5), 275-282. https://doi.org/10.5659/JAIK_PD.2012.28.5.275
  17. Kim, J. R., Son, D. M., & Jung, B. J. (2015). Optimization model for building retrofit planning for energy saving, Journal of the Joint Spring Conference of Korean Institute of Industrial Engineers 2015, 711-718.