A simple model is developed for the estimation of annual rates in single-family houses using indicators for both house tightness (air changes at 50 Pa) and site climate (the leakage-infiltration ratio). This technique is best suited to low-accuracy, large data set problems where detailed data are not available. The method is similar to the method attributed to Kronvall and Persily (ie, the K-P method), but is derived from a physical model, the LBL infiltration model.
Two methods for reducing weather data are assessed and compared with respect to use for heating calculations. Degree days for calendar months, utility bill periods and without weekends were calculated and compared along with temperature 'bins' of various sizes using the CIBSE Example Weather Year. Wind velocity and solar radiation are also analysed with respect to degree days. Both methods, degree days and the bin method, are found to represent the actual weather conditions adequately for use in heating calculations.
This paper summarises the work of the CIBSE Example Year Task Group. Its main task has been to develop a methodology for the selection of representative weather data. This data is required as input to the various procedures available for the estimation of the energy performance of buildings and their engineering systems. As a further aid to applying a consistent set of meteorological data as input to energy calculations, the Task Group's work has extended to the preparation of a set of algorithms for calculating psychrometric properties
In building design the ability to predict the effects of daylight is of increasing importance. Daylight can be an important factor in building energy efficiency; in some buildings lighting may account for half the energy cost. This paper describes the weather data that are available for daylight prediction. First of all the requirements for data are evaluated. For many energy applications, the key quantity is the percentage of the working year a given design illuminance is exceeded by daylight.
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