Abstract
To improve building energy performance and achieve energy conservation, it is significant to predict the energy use in buildings. However, either elaborate engineering methods or simplified statistical methods have their own disadvantages which limit their application. Therefore, this paper presents a new parametric modeling approach to predict building energy based on the combination of engineering method and data monitoring. A reference office building is set up for building energy simulation by parametric analysis. The key influential variables of total energy and sub-level energy can be screened with the optimal subset regression. Then the parametric building energy model is well formulated with regression of the key variables. The established model to predict the building energy consumption has the advantage of considering the main factors and requiring limited parameters input. In the end, the effectiveness of the proposed approach is verified by a real office building.
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References
Zhao, H., Magoulès, F.: A review on the prediction of building energy consumption. Renew. Sustain. Energy Rev. 16(6) (2012)
Chung, W., et al.: Benchmarking the energy efficiency of commercial buildings. Appl. Energy 83(1), 1–14 (2004)
Kissock, J.K., Eger, C.: Measuring industrial energy savings. Appl. Energy 85(5), 347–361 (2008)
Spyrou, M.S., et al.: An empirical study of electricity and gas demand drivers in large food retail buildings of a national organization. Energy Build. 68, 172–182 (2014)
Mathieu, J.L., et al.: Quantifying changes in building electricity use, with application to demand response. IEEE Trans. Smart Grid 2(3), 507–518 (2011)
Kalogirou, S.A., Bojic, M.: Artificial neural networks for the prediction of the energy consumption of a passive solar building. Energy 25(5), 479–491 (2000)
Sha, H., Xu, P.: Establishment of a typical model of Chinese architecture. Shanghai Refrig. Soc. Acad. Annu. Meet. (2011)
Taguchi, G., et al.: Taguchi’s Quality Engineering Handbook. Wiley, Hoboken, NJ (2005)
Qiang, X., et al.: Analysis on energy consumption statistics data of large-scale public buildings in Shanghai. In: Proceedings of the 7th International Green Building and Energy Conservation Conference, China Urban Science Research Association, Bei**g (2011)
Acknowledgements
The study was supported by the National Key R&D Program of China (Grant no. 2017YFC0704200) and National Natural Science Foundation of China Research Award (No.51608370).
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Zhuang, Z., Guo, W. (2020). Parametric Building Energy Modeling Based on Engineering Method and Data Monitoring. In: Wang, Z., Zhu, Y., Wang, F., Wang, P., Shen, C., Liu, J. (eds) Proceedings of the 11th International Symposium on Heating, Ventilation and Air Conditioning (ISHVAC 2019). ISHVAC 2019. Environmental Science and Engineering(). Springer, Singapore. https://doi.org/10.1007/978-981-13-9528-4_39
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DOI: https://doi.org/10.1007/978-981-13-9528-4_39
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