@article {30490, title = {Comparative Study of Air-Conditioning Energy Use of Four Office Buildings in China and USA}, journal = {Energy and Buildings}, volume = {169}, year = {2018}, abstract = {

Energy use in buildings has great variability. In order to design and operate low energy buildings as well as to establish building energy codes and standards and effective energy policy, it is crucial to understand and quantify key factors influencing building energy performance. This study investigates air-conditioning (AC) energy use of four office buildings in four locations: Beijing, Taiwan, Hong Kong, and Berkeley. Building simulation was employed to quantify the influences of key factors, including climate, building envelope and occupant behavior. Through simulation of various combinations of the three influencing elements, it is found that climate can lead to AC cooling consumption differences by almost two times, while occupant behavior resulted in the greatest differences (of up to three times) in AC cooling consumption. The influence of occupant behavior on AC energy consumption is not homogeneous. Under similar climates, when the occupant behavior in the building differed, the optimized building envelope design also differed. Overall, the optimal building envelope should be determined according to the climate as well as the occupants who use the building.

}, keywords = {Building envelope, climate, energy consumption, occupant behavior, office buildings, technological choice}, doi = {10.1016/j.enbuild.2018.03.073}, author = {Xin Zhou and Da Yan and Jingjing An and Tianzhen Hong and Xing Shi and Xing Jin} } @article {59960, title = {Data Analysis and Stochastic Modeling of Lighting Energy Use in Large Office Buildings in China}, journal = {Energy and Buildings}, volume = {86}, year = {2015}, month = {01/2015}, pages = {275-287}, abstract = {

Lighting consumes about 20\% to 40\% of the total electricity use in large office buildings in China. Commonly in building simulations, static time schedules for typical weekdays, weekends and holidays are assumed to represent the dynamics of lighting energy use in buildings. This approach does not address the stochastic nature of lighting energy use, which can be influenced by occupant behavior in buildings. This study analyzes the main characteristics of lighting energy use over various timescales, based on the statistical analysis of measured lighting energy use data from 15 large office buildings in Beijing and Hong Kong. It was found that in these large office buildings, the 24-hourly variation in lighting energy use was mainly driven by the schedules of the building occupants. Outdoor illuminance levels had little impact on lighting energy use due to the lack of automatic daylighting controls (an effective retrofit measure to reduce lighting energy use) and the relatively small perimeter area exposed to natural daylight. A stochastic lighting energy use model for large office buildings was further developed to represent diverse occupant activities, at six different time periods throughout a day, and also the annual distribution of lighting power across these periods. The model was verified using measured lighting energy use from the 15 buildings. The developed stochastic lighting model can generate more accurate lighting schedules for use in building energy simulations, improving the simulation accuracy of lighting energy use in real buildings.

}, keywords = {building simulation, energy use, Lighting modeling, occupant behavior, office buildings, Poisson distribution, stochastic modeling}, doi = {10.1016/j.enbuild.2014.09.071}, author = {Xin Zhou and Da Yan and Tianzhen Hong and Xiaoxin Ren} } @article {56249, title = {Data Analysis and Modeling of Lighting Energy Use in Large Office Buildings}, year = {2013}, abstract = {

Lighting consumes about 20 to 40\% of total electricity use in large office buildings in the U.S. and China. In order to develop better lighting simulation models it is crucial to understand the characteristics of lighting energy use. This paper analyzes the main characteristics of lighting energy use over various time scales, based on the statistical analysis of measured lighting energy use of 17 large office buildings in Beijing and Hong Kong. It was found that the daily 24-hour variations of lighting energy use were mainly driven by the schedule of the building occupants. Outdoor illumination levels have little impact on lighting energy use in large office buildings due to the lack of automatic daylighting controls and relatively small perimeter areas. A stochastic lighting energy use model was developed based on different occupant activities during six time periods throughout a day, and the annual distribution of lighting power across those periods. The model was verified using measured lighting energy use of one selected building. This study demonstrates how statistical analysis and stochastic modeling can be applied to lighting energy use. The developed lighting model can be adopted by building energy modeling programs to improve the simulation accuracy of lighting energy use.

}, keywords = {building simulation, energy use, lighting, modeling, occupant behavior, office buildings, Poisson distribution}, author = {Xin Zhou and Da Yan and Xiaoxin Ren and Tianzhen Hong} }