The use of reduced weather data in predictions of heating energy requirement in buildings

Abstract

This study compares predictions of heating energy requirement for a simple construction during a heating season, using weather data of three different types. The three types are: full seasonal data recorded at hourly intervals, average daily data for each month of the heating season, and daily data averaged over the whole season. A description is given of the hybrid computer system which was used to simulate the thermal performance of the building. Various cases are taken, with a range of values of ventilation rate, glazing area, orientation and daily heating pattern. The predictions of heating energy requirement are compared. It is concluded that, for the range of cases studied, the use of the simplest weather data gives predictions of energy requirement which differ by less than 10% from those obtained using the full hourly data.