Article ID Journal Published Year Pages File Type
764657 Energy Conversion and Management 2010 6 Pages PDF
Abstract

An attempt was made to develop multiple regression models for office buildings in the five major climates in China – severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. A total of 12 key building design variables were identified through parametric and sensitivity analysis, and considered as inputs in the regression models. The coefficient of determination R2 varies from 0.89 in Harbin to 0.97 in Kunming, indicating that 89–97% of the variations in annual building energy use can be explained by the changes in the 12 parameters. A pseudo-random number generator based on three simple multiplicative congruential generators was employed to generate random designs for evaluation of the regression models. The difference between regression-predicted and DOE-simulated annual building energy use are largely within 10%. It is envisaged that the regression models developed can be used to estimate the likely energy savings/penalty during the initial design stage when different building schemes and design concepts are being considered.

Related Topics
Physical Sciences and Engineering Energy Energy (General)
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