A SIMPLIFICATION OF WEATHER DATA TO EVALUATE DAILY AND MONTHLY ENERGY NEEDS OF RESIDENTIAL BUILDINGS

Hourly, daily, monthly and annual heating and cooling requirements of a residential building located in Ottawa, Ontario, Canada were estimated, employing ENERPASS as the energy simulation tool, and performing hour-by-hour energy analysis. The following weather data were employed. (i) Ten years (1967-1976) of weather data. The ten-year average of the results is identified as TYA. (ii) A typical meteorological year (TMY) generated using the same ten years of data. (iii) Two different hourly ambient air temperature distributions (T1 and T2) for a typical day in each month. The solar radiation on each surface was estimated using the mean monthly clearness index. The results of this study show that the long-range hourly, daily, monthly and annual heating and cooling requirements of a residential building located in a cold climate can be predicted by employing mean daily maximum and minimum temperatures and the mean monthly clearness index for each month.