Abstract
Increasing risks of energy security and greenhouse gas emission due to the growing urbanization trend have prompted the need for urban energy demand prediction and management, in which the building energy consumption is the main cause. This paper reviews the recent advances and state-of-the-art in modeling building stock energy consumption, including both the top-down and bottom-up approaches. The study compares and summarizes the strengths and weaknesses of each primary method. Specific focus has been paid to the bottom-up stochastic engineering modeling methods, which hold sound quantitative theory bases as well as considering uncertain reality conditions. Stochastic building stock energy models account for the uncertainties that are the main limitation in existing building stock models. Discussions are provided regarding the process in the current stochastic building stock energy model. Challenges and possible future directions are examined for the improvement of stochastic building stock energy model.
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Acknowledgements
The research presented in this paper was supported by the US National Science Foundation (EFRI-1038305), and the national key project of the Ministry of Science and Technology, China, on “Green Buildings and Building Industrialization” through Grant No. 2016YFC0700500, as well as the Department of Civil, Environmental and Architectural Engineering Doctoral Assistantship for Completion of Dissertation at University of Colorado Boulder (Spring 2016).
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Lim, H., Zhai, Z.J. Review on stochastic modeling methods for building stock energy prediction. Build. Simul. 10, 607–624 (2017). https://doi.org/10.1007/s12273-017-0383-y
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DOI: https://doi.org/10.1007/s12273-017-0383-y