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A quantitative comparison of different methods for air conditioning energy consumption prediction in residential buildings

Du, C., Ao, J., Li, B., Chen, Z. and Essah, E. ORCID: https://orcid.org/0000-0002-1349-5167 (2024) A quantitative comparison of different methods for air conditioning energy consumption prediction in residential buildings. Energy and Built Environment. ISSN 2666-1233 (In Press)

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To link to this item DOI: 10.1016/j.enbenv.2024.11.007

Abstract/Summary

Accurate evaluation of energy consumption of air conditioning (AC) is crucial to energy efficiency in residential buildings, while few studies evaluate quantitatively the differences of the currently used methods. This study aimed to assess two common methods for AC energy consumption evaluation, namely, top-down total energy disaggregation and bottom-up energy simulation, through comparing to field measurement. A longitudinal investigation was conducted in residences in Chongqing, a typical city in the Hot Summer and Cold Winter(HSCW) zone. The yearly daily electricity consumption of 18 residences were collected and wireless sensors and smart sockets were used for onsite measurement. The AC energy consumption was obtained by splitting the total electricity consumption and measurements. Moreover, three typical reference buildings were built for predicting the annual AC energy consumption. Results showed that the simulated AC energy consumption was about 2.76 times of the measured value; while it was about 2.89 times for the top-down disaggregation method. Some key factors influencing AC energy consumption (e.g., indoor temperature distribution, opening duration, AC usage frequency) were identified for different methods. The work quantified the limitations of the top-down and bottom-up methods, contributing to the improvement of AC energy consumption evaluation methods and management of heating and cooling energy in residential buildings.

Item Type:Article
Refereed:Yes
Divisions:Science > School of the Built Environment > Construction Management and Engineering
Science > School of the Built Environment > Energy and Environmental Engineering group
ID Code:119722
Publisher:Elsevier

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