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Renewable Energy
Article . 2020 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Collaborative optimization between passive design measures and active heating systems for building heating in Qinghai-Tibet plateau of China

Authors: Bo Lei; Haiquan Bi; Xiaoliang Wang; Xiaoliang Wang; Gang Mao; Xianmin Mai; Bing Zhao;

Collaborative optimization between passive design measures and active heating systems for building heating in Qinghai-Tibet plateau of China

Abstract

Abstract Due to cold winter and cool summer in Qinghai-Tibet plateau, heating energy consumption accounts for a large proportion in the building energy consumption and reducing heating energy consumption is one of the main energy-saving methods for buildings. In the process of building heating, passive design measures and active heating systems (AHS) are always working together. To optimize the heating performance, it is necessary to coordinate the relationship between passive design measures and the AHS. However, it is impossible to obtain the specific quantitative optimized relationship between passive design measures and AHS based on existing research methods. To address this lack of knowledge, a collaborative optimization design method (CODM) is proposed in this paper to optimize the cost and the energy consumption of heating in the life cycle of the building. In CODM, comprehensive effects of passive design measures and the AHS on the total cost and the total energy consumption for building heating are analyzed. A railway passenger station is selected as a case study and results show that compared with initial design, the optimal total heating cost and total heating energy consumption for building heating can reduce 1948 ¥/m2 and 2292 kW h/m2 for the life cycle of the building, respectively.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
35
Top 10%
Top 10%
Top 10%