An eQUEST Based Building Energy Modeling Analysis for Energy Efficiency of Buildings

Abstract

Building energy performance is a function of numerous building parameters. In this study, sensitivity analysis on twenty parameters is performed to determine the top three parameters which have the most significant impact on the energy performance of buildings. Actual data from two fully operational commercial buildings were collected and used to develop a building energy model in eQUEST. The model is calibrated using Normalized Mean Bias Error (NMBE) and Coefficient of Variation of Root Mean Square Error (CV(RMSE)) method. The model satisfies the NMBE and CV(RMSE) criteria set by the American Society of Heating, Refrigeration, and Air-Conditioning (ASHRAE) Guideline 14, Federal Energy Management Program (FEMP), and International Performance Measurement and Verification Protocol (IPMVP) for building energy model calibration. The values of the parameters are varied in two levels, and then the percentage change in output is calculated. Fractional factorial analysis on eight parameters with the highest percentage change in energy performance is performed at two levels in a statistical software JMP. For Building A, top 3 parameters from percentage change method are: Heating setpoint, cooling setpoint and server room. From fractional factorial design, top 3 parameters are: heating setpoint (p-value= 0.00129), cooling setpoint (p-value= 0.00133), and setback control (p-value= 0.00317). For Building B, top 3 parameters from both methods are: Server room (p-value= 0.0000), heating setpoint (p-value= 0.00014), and cooling setpoint (p-value= 0.00035). If the best values for all top three parameters are taken simultaneously, energy efficiency improves by 29% for Building A and 35 % for Building B.