scholarly journals The reality and future scenarios of commercial building energy consumption in China

2008 ◽  
Vol 40 (12) ◽  
pp. 2121-2127 ◽  
Author(s):  
Nan Zhou ◽  
Jiang Lin
2015 ◽  
Vol 74 (4) ◽  
Author(s):  
Atefeh Mohammadpour ◽  
Mohammad Mottahedi ◽  
Shideh Shams Amiri ◽  
Somayeh Asadi ◽  
David Riley ◽  
...  

Building energy modeling is essential to estimate energy consumption of buildings. Predicting building energy consumption benefits the owners, designers, and facility managers by enabling them to have an overview of building energy consumption and can help them to determine building energy performance during the design phase. This paper focuses on two different shapes of commercial building, H and rectangle to estimate energy consumption in buildings in three different climate zones, cold, hot-humid, and mixed-humid. To address this, DOE-2 building simulation software was used to build and simulate individual commercial building configurations that were generated using Monte Carlo simulation techniques. Ten thousand simulations for each building shape and climate zone were conducted to develop a comprehensive dataset covering the full range of design parameters. 


Energy ◽  
2021 ◽  
Vol 214 ◽  
pp. 119063
Author(s):  
Siyue Guo ◽  
Da Yan ◽  
Shan Hu ◽  
Yang Zhang

2021 ◽  
Vol 257 ◽  
pp. 02060
Author(s):  
Yanwei Wang ◽  
Hanyuan Zhang ◽  
Guiqing Zhang ◽  
Feng Tian ◽  
Fei Ren

The analysis of building abnormal energy consumption is of great significance to the effective energy saving of buildings. To apply the relationship between the running status of building equipment and energy consumption to the diagnosis of abnormal energy consumption, an abnormal diagnosis method of building energy consumption based on the improved Apriori association rules is proposed. An improved Apriori algorithm is proposed for building energy consumption data with a large amount of data and multi-value attributes. The improved Apriori algorithm determines whether different attribute values of the same attribute data are in advance when generating candidate sets, reduces the number of comparisons, and improves the algorithm efficiency. By analyzing the abnormal energy consumption of the chiller in the refrigeration station of a commercial building, the superiority of the improved Apriori algorithm is proved, and the abnormal energy consumption is found, which verifies the feasibility and practicability of the proposed method.


2017 ◽  
Vol 208 ◽  
pp. 889-904 ◽  
Author(s):  
Caleb Robinson ◽  
Bistra Dilkina ◽  
Jeffrey Hubbs ◽  
Wenwen Zhang ◽  
Subhrajit Guhathakurta ◽  
...  

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