01954nas a2200241 4500008004100000245009500041210006900136490000800205520119700213653002201410653001201432653002301444653002201467653002101489653002501510100001401535700001201549700001701561700001901578700001401597700001401611856008701625 2018 eng d00aComparative Study of Air-Conditioning Energy Use of Four Office Buildings in China and USA0 aComparative Study of AirConditioning Energy Use of Four Office B0 v1693 a

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.

10aBuilding envelope10aclimate10aenergy consumption10aoccupant behavior10aoffice buildings10atechnological choice1 aZhou, Xin1 aYan, Da1 aAn, Jingjing1 aHong, Tianzhen1 aShi, Xing1 aJin, Xing uhttps://simulationresearch.lbl.gov/publications/comparative-study-air-conditioning02384nas a2200253 4500008003900000245010000039210006900139260001200208300001200220490000700232520158600239653002401825653001501849653002201864653002201886653002101908653002501929653002401954100001401978700001201992700001902004700001702023856009002040 2015 d00aData Analysis and Stochastic Modeling of Lighting Energy Use in Large Office Buildings in China0 aData Analysis and Stochastic Modeling of Lighting Energy Use in  c01/2015 a275-2870 v863 a

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.

10abuilding simulation10aenergy use10aLighting modeling10aoccupant behavior10aoffice buildings10aPoisson distribution10astochastic modeling1 aZhou, Xin1 aYan, Da1 aHong, Tianzhen1 aRen, Xiaoxin uhttps://simulationresearch.lbl.gov/publications/data-analysis-and-stochastic-modeling02003nas a2200217 4500008003900000245008000039210006900119520131400188653002401502653001501526653001301541653001301554653002201567653002101589653002501610100001401635700001201649700001701661700001901678856008801697 2013 d00aData Analysis and Modeling of Lighting Energy Use in Large Office Buildings0 aData Analysis and Modeling of Lighting Energy Use in Large Offic3 a

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.

10abuilding simulation10aenergy use10alighting10amodeling10aoccupant behavior10aoffice buildings10aPoisson distribution1 aZhou, Xin1 aYan, Da1 aRen, Xiaoxin1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/data-analysis-and-modeling-lighting