Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China. (1st June 2017)

• Record Type: Journal Article
• Authors: Cui, Ying; Yan, Da; Hong, Tianzhen; Xiao, Chan; Luo, Xuan; Zhang, Qi
• Is Part Of: Applied energy. Volume 195(2017)
• Page Start: 890
• Page End: 904
• Publication Date: 2017-06-01
• Subjects: Typical year -- Multiyear simulation -- Actual weather data -- Building simulation -- Energy use -- Peak load; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2017.03.113
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: The typical year and multiyear building simulation are compared. Total 559 simulation runs of a prototype office building for 10 large cities are performed. The weather data varied significantly year-over-year. The representative of typical year simulation on building energy use and peak load is studied. It is recommended to using multiyear weather data for building design and performance simulation. Abstract: Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this study, the long-term representation of a typical year was assessed by comparing it to a 55-year actual weather data set. To investigate the weather impact on building energy use, 559 simulation runs of a prototype office building were performed for 10 large cities covering all climate zones in China. The analysis results demonstrated that the weather data varied significantly from year to year. Hence, a typical year cannot reflect the variation range of weather fluctuations. Typical year simulations overestimated or underestimated the energy use and peak load in many cases. With the increase in computational power of personal computers, it is feasible and essential to adopt multiyear simulations for full assessments of long-term building performance, as this will improve decision-making by allowing for the full consideration of variations in building energy use.