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

• Two methods for AC energy consumption prediction were quantitatively compared. • Measured AC energy consumption was 2.62kWh/d for cooling and 0.47kWh/d for heating. • Values by top-down decomposition method were about 2.89 times of actual values. • The results obtained by bottom-up simulation was about 2.76 times higher. • AC usage patterns and other household appliances were the key factors. 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.

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Publication Details

Journal
Energy and Built Environment
Published
2024-11-23
DOI
https://doi.org/10.1016/j.enbenv.2024.11.007
Citations
4
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
1.06
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article

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

Emmanuel Essah, Baizhan Li, Jingyun Ao, Zhaoyang Chen et al.
4 citations
Energy and Built Environment
Building Energy and Comfort Optimization
1.06
article

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

Emmanuel Essah, Baizhan Li, Jingyun Ao, Zhaoyang Chen, Chenqiu Du
article en
4 citations

Abstract

• Two methods for AC energy consumption prediction were quantitatively compared. • Measured AC energy consumption was 2.62kWh/d for cooling and 0.47kWh/d for heating. • Values by top-down decomposition method were about 2.89 times of actual values. • The results obtained by bottom-up simulation was about 2.76 times higher. • AC usage patterns and other household appliances were the key factors. 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.

Energy and Built EnvironmentVol. 7(2)
Chongqing University (CN), University of Reading (GB)
Affordable and clean energy
Openalex Percentile: Top 24%
Building Energy and Comfort Optimization
1.06
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