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A procedure for the performance rvaluation of a new commercial building: part I--calibrated as-built simulation.

Article Excerpt
INTRODUCTION

Many building energy studies and ASHRAE research projects have been reporting on efforts to calibrate simulations to measured data from monthly utility data (Diamond and Hunn 1981; McLain et al., 1994), and to hourly measured data (Hsieh 1988; Kaplan et al. 1990, 1992; Bronson et al. 1992; Huang 1994; Haberl et al. 1995; Huang and Crawley 1996; Haberl and Bou-Saada 1998; Abushakra 2001; Reddy 2004; Ramirez 2006). In addition, in-situ measurements of HVAC&R equipment (Phelan et al. 1997a, 1997b; Haberl et al. 1997; Liu et al. 2002) have been developed to support the effectiveness of calibrated simulation.

Some of the earliest published calibration procedures were developed in the two office buildings reported by Hsieh (1988), including: calibration of tenant energy use, HVAC equipment operation schedules and thermostat setpoints, heating and cooling equipment performance, building shell heat loss coefficient, zone definitions in DOE-2, outside air intake, and weather data. Of these factors, the calibration technique for equipment performance was used in this study because the DOE-2 program only provides standard default performance values that may not be related to the high efficiency equipment installed in a building.

Kaplan et al. (1990) developed "day-type schedules" to incorporate monitored lighting and equipment data into the typical operating schedule in the DOE-2 model. Such day-type schedules showed that monitored data could be used to generate simulation inputs, as well as to verify simulation outputs for calibrating the simulation model. Abushakra et al. (2001) completed ASHRAE research project 1093-RP for developing procedures to derive diversity factors and typical load shapes of lighting and receptacle loads in office buildings. In their study, a percentile analysis was used to derive load shapes and diversity factors, which were used in the current study. Recently, as an integral part of the California Energy Commission Commercial End-Use Survey(CEC CEUS) effort, a Site Processor (Ramirez 2006) has been developed to interface survey data with the building simulation processor(eQuest) for the purpose of site simulation and calibration to actual energy consumption data. In the site processor, four day-types defined in the 16-day format were used to make adjustments to whole end uses, which are similar to the load and diversity factors used in the current study.

Haberl et al. (1995) evaluated the impact of using measured weather data that was repacked into Test Reference Year (TRY) format vs. TMY format in a DOE-2 simulation by comparing the results of simulated energy use. Huang and Crawley (1996) also compared the influence of the various weather data sets, including: TRY, TMY, TMY2, WYEC (Weather Year for Energy Calculations), and WYEC2, on simulated annual energy use and energy cost. Huang and Crawley (1996) recommended that TMY2 (Marion and Urban 1995) should be used in building energy simulations where solar radiation is critical to the results. The results from both of these studies have provided guidance to the current study.

An effective calibrated simulation often requires in-situ performance measurements of the mechanical equipment, especially for high efficiency equipment that is used for new high performance buildings. To assist in this effort, Phelan et al. (1997b) developed a set of in-situ testing methods for pumps, fans, and chillers under ASHRAE Research Project 827-RP to evaluate annual energy consumption and to account for part-load operations that are affected by overall system controls. They developed semi-empirical chiller models using a statistical regression analysis based on one year of hourly measured data, including: chiller power consumption, evaporator flow rates, and chilled water and condenser water supply and return temperature, which proved to be useful in the current study. Liu et al. (2002) developed a procedure to determine the in-situ performance of commonly used HVAC systems as part of ASHRAE Research Project 1092-RP. In their project, the research objectives were to develop a simplified model calibration procedure from short-term field measurement and validate the calibration procedure using a simulation program developed with the ASHRAE modified bin method, which was useful to this study.

Finally, several statistical methods have been developed to access the goodness-of-fit of a simulation model, including: percent difference, mean bias error (MBE), and the coefficient of variation of the root mean square error (CV(RMSE)) (Kreider and Haberl 1994), which were used in the current study. Graphical comparisons are also useful to effectively represent the difference between simulated and measured data. In relation, Wei et al. (1998) developed "calibration signatures" of different parameters on the heating and cooling energy consumption of typical air handling units (AHUs) for model calibration. In this study, the signature concept is enhanced with...

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