库存(枪支)
高效能源利用
计算机科学
电
气候变化
环境经济学
环境科学
工程类
经济
机械工程
生态学
电气工程
生物
作者
Yohei Yamaguchi,Bumjoon J. Kim,Takuya Kitamura,Kotone Akizawa,Hemiao Chen,Yoshiyuki Shimoda
出处
期刊:Applied Energy
[Elsevier]
日期:2022-01-01
卷期号:306: 117907-117907
被引量:25
标识
DOI:10.1016/j.apenergy.2021.117907
摘要
A significant improvement in the building stock energy efficiency is imperative to mitigate climate change. Building stock energy models (BSEMs) that employ reference building models are useful for mitigation analysis. However, most existing BSEMs developed for commercial building stock focus on limited building systems and energy conservation measures, and technology deployments are suggested based on simple vintage-driven scenarios. These approaches are insufficient, particularly for regions where improvements to building insulation performances can have a modest impact. This study aims to establish a BSEM framework to overcome this issue and to validate the framework via its application to the Japanese commercial building stock. The framework develops statistical models for estimating the selection probabilities of system alternatives and utilizes them to disaggregate building stocks. A reference building model is developed for each stock segment. The results show that this approach facilitates the use of multiple technological options considering various factors that affect technological deployments, and it also helps estimate the baseline development of building stocks. Furthermore, the developed model well represents the observed distributions in energy use intensity and estimates the aggregated energy consumption of building stocks with a reasonable accuracy. The baseline development was estimated to reduce the CO2 emission by 18% by 2030 from 2013. Efficiency measures can help avoid the increase in electricity demand caused by electrifying the heat source of heating, ventilating, and air-conditioning and water heating systems. The framework could help extend the scope of BSEM application because BSEM development is not information intensive.
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