Effects of Geometric Parameters on Energy Performance of Residential Buildings in Severely Cold Areas

doi:10.23940/ijpe.20.09.p16.14681477

Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (9): 1468-1477.doi: 10.23940/ijpe.20.09.p16.14681477

Previous Articles Next Articles

Effects of Geometric Parameters on Energy Performance of Residential Buildings in Severely Cold Areas

Jiaying Teng^a,b,*, Wan Wang^a, Xijie Ai^a, Han Yang^a, and Lianqiang Zhang^a

^aSchool of Economics and Management, Jilin Jianzhu University, Changchun, 130118, China;
^bCreative Centre for ArtSciArch, Jilin Jianzhu University, Changchun, 130118, China

Submitted on ; Revised on ; Accepted on
Contact: * E-mail address: jiaying1016@foxmail.com
About author:Jiaying Teng is an associate professor in the School of Economics and Management at Jilin Jianzhu University. Her research interests include green building, computer simulation, and information analysis.
Wan Wang is a lecturer in the School of Economics and Management at Jilin Jianzhu University. Her research interests include green building and information analysis.
Xijie Ai is a master's student in the School of Economics and Management at Jilin Jianzhu University. His research interests include green building and information analysis.
Han Yang is a master's student in the School of Economics and Management at Jilin Jianzhu University. Her research interests include green building and information analysis.
Lianqiang Zhang is a master's student in the School of Economics and Management at Jilin Jianzhu University. His research interests include green building and information analysis.

Abstract

Abstract: The energy demands for heating have been increasing rapidly in Northern China. To improve the energy efficiency of residential buildings in Changchun, a major city in Northeast China, a residential building model is constructed in the DesignBuilder software and used to assess the effects of geometric parameters including floor height and window-to-wall ratio on the energy performance of residential buildings. The simulation is conducted with the parameters of both traditional plan and alternative plans to calculate the energy consumption of each plan and evaluate the parameters. Based on the simulation results, the most optimal geometric parameters of the residential building model are proposed. The floor height of 2.8 m gives the highest energy-saving efficiency in the tested range. The optimal window-to-wall ratios of the north wall, south wall, east wall, and west wall of the building model are determined to be 0.25, 0.45, 0.30, and 0.30, respectively. Our study identifies an efficient passive design plan upon the geometric parameters of residential buildings in severely cold areas and provides a theoretical reference for decision-making in the early design stage.

Key words: passive design, energy efficiency, simulation

Jiaying Teng, Wan Wang, Xijie Ai, Han Yang, and Lianqiang Zhang. Effects of Geometric Parameters on Energy Performance of Residential Buildings in Severely Cold Areas [J]. Int J Performability Eng, 2020, 16(9): 1468-1477.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

References

1. H. Z. Liu, H. T. Ding, T. Y. Li, et al., “Research on the Status Quo and Development Trend of Energy Consumption of Civil Buildings,”Construction Science and Technology, Vol. 8, pp. 10-11, 2018
2. S. M.Ibbotson and S. Kara, “An Approach to Identify the Factors that Affect a Products Life Time Energy Consumption During the Concept Design Stage,” inProceedings of 28TH CIRP Design Conference, Vol. 70, pp. 223-228, 2018
3. E. Elbeltagi, H. Wefki, S. Abdrabou, M. Dawood,A. Ramzy, “Visualized Strategy for Predicting Buildings Energy Consumption During Early Design Stage using Parametric Analysis,”Journal of Building Engineering, Vol. 13, pp. 127-136, 2017
4. E. Eliopoulou and E. Mantziou, “Architectural Energy Retrofit (AER): An Alternative Building's Deep Energy Retrofit Strategy,”Energy and Buildings, Vol. 150, pp. 239-252, 2017
5. K. J. Kontoleon, “Energy Saving Assessment in Buildings with Varying Façade Orientations and Types of Glazing Systems When Exposed to Sun,” International Journal of Performability Engineering, Vol. 9, No. 1, pp. 33-48, 2013
6. C. P. Liu, W. Xu, A. G. Li, D. Y. Sun,H. M. Huo, “Energy Balance Evaluation and Optimization of Photovoltaic Systems for Zero Energy Residential Buildings in Different Climate Zones of China,”Journal of Cleaner Production, Vol. 235, pp. 1202-1215, 2019
7. G. L.Szabo and F. Kalmar, “Investigation of Energy and Exergy Performances of Radiant Cooling Systems in Buildings - A Design Approach,”Energy, Vol. 185, pp. 449-462, 2019
8. J. Egan, D. Finn, P. H. D.Soares, V. A. R. Baumann, R. Aghamolaei, P. Beagon, et al., “Definition of a Useful Minimal-Set of Accurately-Specified Input Data for Building Energy Performance Simulation,”Energy and Buildings, Vol. 165, pp. 172-183, 2018
9. J. Y. Teng and Y. D. Liu, “Study on Energy-Saving Contribution of Passive Retrofit Measures of Public Building in a Severely Cold Area,” New Building Materials, Vol. 2017, No. 3, pp. 90-93, 2017
10. S. B. Sadineni, S. Madala,R. F. Boehm, “Passive Building Energy Savings: A Review of Building Envelope Components,” Renewable and Sustainable Energy Reviews, Vol. 15, No. 8, pp. 3617-3631, 2011
11. X. H.Du and B. Jia, “Discussion on Applying Trombe Wall Technology for Wall Conservation and Energy Saving in Modern Historic,” International Journal of Architectural Heritage, Vol. 13, No. 4, pp. 537-548, 2019
12. N. Cardinale, M. Micucci,F. Ruggiero, “Analysis of Energy Saving using Natural Ventilation in a Traditional Italian Building,” Energy and Buildings, Vol. 35, No. 2, pp. 153-159, 2003
13. H. E.Zirnhelt and R. C. Richman, “The Potential Energy Savings from Residential Passive Solar Design in Canada,”Energy and Buildings, Vol. 103, pp. 224-237, 2015
14. E. Cuce and S. B. Riffat, “A State-of-the-Art Review on Innovative Glazing Technologies,”Renewable and Sustainable Energy Reviews, Vol. 41, pp. 695-714, 2015
15. F. Goia, “Search for the Optimal Window-to-Wall Ratio in Office Buildings in Different European Climates and the Implications on Total Energy Saving Potential,”Solar Energy, Vol. 132, pp. 467-492, 2016
16. A. X. Zhang, R. Bokel, A. V. D.Dobbelsteen, Y. Sun, Q. Huang, and Q. Zhang, “The Effect of Geometry Parameters on Energy and Thermal Performance of School Buildings in Cold Climates of China,”Sustainability, Vol. 9, pp. 1-19, 2017
17. K. T.Chan and W. K. Chow, “Energy Impact of Commercial-Building Envelopes in the Sub-Tropical Climate,” Applied Energy, Vol. 60, No. 1, pp. 21-39, 1998
18. C. Balaras, P. Droutsa, A. A. Argiriou,D. N. Asimakopoulos, “Potential for Energy Conservation in Apartment Buildings,” Energy and Buildingsm, Vol. 31, No. 2, pp. 143-54, 2000
19. X. Chen, H. X. Yang,L. Lu, “A Comprehensive Review on Passive Design Approaches in Green Building Rating Tools,”Renewable and Sustainable Energy Reviews, Vol. 50, pp. 1425-1436, 2015
20. MOHURD (Ministry of Housing and Urban-Rural Development of the People's Republic of China), GB/T 51161-2016, “Standard for Energy Consumption of Building,” China Construction Industry Publishing House, Beijing, 2016
21. T. Hong, H. Kim,T. Kwak, “Energy-Saving Techniques for Reducing CO2 Emissions in Elementary Schools,”Journal of Management in Engineering, Vol. 28, pp. 39-50, 2012
22. S. B. Sadineni, T. M. France,R. F. Boehm, “Economic Feasibility of Energy Efficiency Measures in Residential Buildings,”Renewable Energy, Vol. 36, pp. 2925-2931, 2011

[1]	Junhua Yue and Yan Li. Simulation for Target Detection in Polarimetric Scenes [J]. Int J Performability Eng, 2020, 16(8): 1310-1320.
[2]	Manish Rawat and Bhupesh Kumar Lad. Joint Optimization of Reliability Design and Level of Repair Analysis Considering Time Dependent Failure Rate of Fleet System [J]. Int J Performability Eng, 2020, 16(6): 821-833.
[3]	Chunyuan Shi, Chen Chen, Zhilong Yu, and Ran Li. Control Strategy of Hybrid Electric Vehicle based on Threshold Control [J]. Int J Performability Eng, 2020, 16(3): 462-469.
[4]	Jiamei Niu, Xuan Zhang, Ziqi Tang, Jingzhuan Zhao. System Dynamics Simulation of Global Software Development Process [J]. Int J Performability Eng, 2020, 16(2): 171-184.
[5]	Siyu Li, Shaoluo Huang, Yangyang Zhang, Lijun Cao, and Weiyi Wu. Deep Learning in Fault Diagnosis of Complex Mechanical Equipment [J]. Int J Performability Eng, 2020, 16(10): 1548-1555.
[6]	Jiuxia Guo, Shuzhi Sam Ge, Xinping Zhu, and Fangfang Zhao. Modeling of ATC Operation Process based on Extended Colored Petri Net [J]. Int J Performability Eng, 2019, 15(9): 2522-2533.
[7]	Ananthakrishnan Kaimal, Bevin Boban Mathew, and S. Jeyanthi. Homogeneous Metal Foam Manufacturing and Impact Test Performance [J]. Int J Performability Eng, 2019, 15(8): 2040-2048.
[8]	Zhigang Liu, Zhongxiang Ma, Gengjin Sui, Dejian Zou, and Guoliang Li. Optimization Design and Reliability Analysis of Salix Cutting Tools based on Finite Element Method [J]. Int J Performability Eng, 2019, 15(2): 441-453.
[9]	Mourad Chebila. Non-Intrusive Polynomial Chaos for a Realistic Estimation of Accident Frequency [J]. Int J Performability Eng, 2019, 15(11): 2852-2859.
[10]	Lijun Cao, Tong Xu, Chao Ding, Guibo Yu, and Shuhai Wang. Design and Realization of Reliability Enhancement Test for Breech Mechanism of Large-Caliber Guns [J]. Int J Performability Eng, 2019, 15(1): 116-126.
[11]	Sa Meng, Xiwei Qiu, Liang Luo, Han Xu, and Meilian Lei. Reliability Simulation in Cloud Computing System [J]. Int J Performability Eng, 2018, 14(9): 2015-2020.
[12]	Junxi Bi, Chenglong Zheng, Hongzhong Huang, Yan Zhou, and Xiaoxue Li. Load Analysis and Calculation Optimization of Horizontal Axis Wind Turbine Blades [J]. Int J Performability Eng, 2018, 14(12): 3098-3108.

Effects of Geometric Parameters on Energy Performance of Residential Buildings in Severely Cold Areas

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 12

Recommended 10