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The conventional typical meteorological year (TMY) based on continuous-year original meteorological records without considering abrupt climate changes (ACC) may not be able to represent a real "typical" climate properly. Consequently, building performance analyses and simulations based on TMY may be not accurate. Current research rarely tackles this issue in TMY development. This paper presents an innovative TMY development with the consideration of ACC in the original meteorological records. It is based on the Chinese standard weather database method (CSWD) with the meteorological records of six Chinese cities in different climate zones. It applies the Moving t-test method to identify and exclude ACC points and to refine the timescales for TMY development. It also depicts the development of individual typical meteorological months again with the ACC impact to improve the accuracy of TMY. The method has been verified in several building energy consumption and thermal comfort analyses. The results demonstrate that the analysis based on the new TMY climate datasets when considering ACC will end up with less energy consumption and better thermal performance compared to the analyses based on the conversion dataset without considering ACC. This experimental research will refine TMY development, and further improve building energy performance analysis and design. [ABSTRACT FROM AUTHOR]

Energy performance of buildings is a worldwide increasing investigated field, due to ever more stringent energy standards aimed at reducing the buildings' impact on the environment. The purpose of this paper is to assess the impact that occupant behavior and climate change have on the heating and cooling needs of residential buildings. With this aim, data of a questionnaire survey delivered in Southern Italy were used to obtain daily use profiles of natural ventilation, heating, and cooling, both in winter and in summer. Three climatic scenarios were investigated: The current scenario (2020), and two future scenarios (2050 and 2080). The CCWorldWeatherGen tool was used to create the weather files of future climate scenarios, and DesignBuilder was applied to conduct dynamic energy simulations. Firstly, the results obtained for 2020 demonstrated how the occupants' preferences related to the use of natural ventilation, heating, and cooling systems (daily schedules and temperature setpoints) impact on energy needs. Heating energy needs appeared more affected by the heating schedules, while cooling energy needs were mostly influenced by both natural ventilation and usage schedules. Secondly, due to the temperature rise, substantial decrements of the energy needs for heating and increments of cooling energy needs were observed in all the future scenarios where in addition, the impact of occupant behavior appeared amplified. [ABSTRACT FROM AUTHOR]