Development of an automated methodology for calibration of building energy systems simplified simulation
The modeling of the building energy use is a significant component of the success of conservation programs; therefore, several techniques and simulation programs have been developed to accomplish this purpose. By and large, it is accepted that simulations and/or statistical modeling of daily, or monthly, energy use are appropriate for determining retrofit savings, while the hourly energy use scale may be used for performing more detailed analysis, such as fault diagnosis and optimization. On the other hand, calibrated simulations can be used for purposes of application of energy efficient measures and on automated methodology could reduce substantial amount of time which always is required in this process adding more accuracy. This paper presents the development of an automated calibration methodology of building energy systems simplified air-side heating ventilation and air condition (HVAC) system with minimum, or limited information, of the building characteristics and operational control. The methodology has been tested successfully on building simulations based on the simplified energy analysis procedure. The automated calibration is based on the minimization of the root mean square error (RMSE) of the energy use over daily conditions between measure data and the results generated by the simplified simulation. The focus of the automated calibration procedure is on the temperature-dependent energy use, such as the whole-building heating and cooling use. The minimization procedure is fulfilled with a non-canonical optimization algorithm, the Simulated Annealing, which mimics the Statistical Thermodynamic performance of the annealing process. That is to say, starting at a specified temperature the algorithm searches variable-space states that are steadier, while heuristically, by the Boltzmann distribution, the local minima is avoided. The process is repeated at a new lower temperature that is determined by a specific schedule until the global minimum is found. The methodology was tested on the most common air-handler units producing excellent results for ideal cases or for samples. The four major generic types of commercial building air handling units (AHU) that are included in this research are: the Dual Duct Constant Volume (DDCV), the Dual Duct Variable Air Volume (DDVAV), the Single Duct Constant Volume (SDCV), and the Single Duct Variable Air Volume (SDVAV) systems. There are variations of each of these major system types, but those systems are beyond the scope of this work. The methodology was tested on synthetic cases, based on real samples modified with different ranges of added white noise, and real cases. The results indicated that the methodology is steady and cases with low, below 5%, white noise and for the steady operated conditions are satisfactory.
author list (cited authors)
Baltazar, J. C., Claridge, D. E., & Hernandez-Guerrero, A.