We have developed an algorithm to disaggregate short-interval (hourly) whole-building electrical load into major end uses. Hourly load data, hourly load-temperature regression coefficients and simulation end-use results comprise the algorithm input. The algorithm produces hourly load profiles for air conditioning, lighting, fans and pumps, and miscellaneous loads. Measured data from two end-use metered buildings (an office and a retail store) have been used to validate the algorithm. For the retail store, the algorithm estimates of hourly end use compare remarkably well with the monitored end-use data (average error of less than 5% during daytime operation). For the office building, the algorithm gives a consistent bias of about 12 and 27% in overestimating the HVAC and lighting electric loads, respectively, at the expense of underestimating the miscellaneous load by 35%. Results may be attributed to the presence of inconsistencies between office audit information and measured end-use data. A three-fold difference between the auditor＇s estimate for miscellaneous energy use and the metered amount has been found. The validation, however, indicates great promise for application of the algorithm to whole-building load data for obtaining reliable end-use data.