PROCEDURES FOR CALIBRATING HOURLY SIMULATION-MODELS TO MEASURED BUILDING ENERGY AND ENVIRONMENTAL DATA

This paper discusses procedures for creating calibrated building energ y simulation programs. It begins with reviews of the calibration techn iques that have been reported in the previous literature and presents new hourly calibration methods including a temperature bin analysis to improve hourly x-y scatter plots, a 24-hour weather-daytype bin analy sis to allow for the evaluation of hourly temperature and schedule dep endent comparisons, and a 52-week bin analysis to facilitate the evalu ation of long-term trends. In addition, architectural rendering is rev iewed as a means of verifying the dimensions of the building envelope and external shading placement as seen by the simulation program. Seve ral statistical methods are also presented that provide goodness-of-fi t indicators, including percent difference calculations, mean bias err or (MBE), and the coefficient of variation of the root mean squared er ror (CV(RMSE)). The procedures are applied to a case study building lo cated in Washington, D.C. where nine months of hourly whole-building e lectricity data and site-specific weather data were measured and used with the DOE-2.1D building energy simulation program to test the new t echniques. Simulations that used the new calibration procedures were a ble to produce an hourly MBE of -0.7% and a CV(RMSE) of 23.1% which co mpare favorably with the most accurate hourly neural network models (K reider and Haberl, 1994a, b).