A Repetitive Day Method for Predicting the Long-Term Thermal Performance of Passive Solar Buildings

Abstract

The long-term thermal performance of passively-heated solar buildings is predicted by a single repetitive meteorological day which contains judiciously chosen solar radiation and ambient temperature functions. These are used as the driving functions of the governing equations that describe the passive solar building under study. The solar radiation and ambient temperature functions are chosen such that they include, both qualitatively and quantitatively, the essential radiation and temperature statistics of the climate in which the building is to be located. The relevant statistics are determined from hourly meteorological data. When hourly meteorological data are not available for a given location, the solar radiation and ambient temperature functions can be constructed from the knowledge of only two climatic data, namely, the monthly average horizontal radiation and the ambient temperature. Model calculations compare favorably with experimental data from Los Alamos solar test cells and with computer simulations.