Development of an automated methodology for calibration of simplified air-side HVAC system models and estimation of potential savings from retrofit/commissioning measures
This dissertation provides one methodology to determine potential energy savings
of buildings with limited information. This methodology is based upon the simplified
energy analysis procedure of HVAC systems and the control of the comfort conditions.
Numerically, the algorithm is a tailored exhaustive search over all the independent
variables that are commonly controlled for a specific type of HVAC system. The
potential energy savings methodology has been applied in several buildings that have
been retrofitted and/or commissioned previously. Results from the determined savings
for the Zachry building at Texas A&M after being commissioned show a close
agreement to the calculated potential energy savings (about 85%). Differences are
mainly attributed to the use of simplified models.
Due to the restriction of limited information about the building characteristics and
operational control, the potential energy savings method requires the determination of
parameters that characterize its thermal performance. Thus, a calibrated building is
needed. A general procedure has been developed to carry out automated calibration of
building energy use simulations. The methodology has been tested successfully on
building simulations based on the simplified energy analysis procedure. The automated
calibration is the minimization of the RMSE of the energy use over daily conditions.
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. This methodology was applied to the most common air-handler units producing
excellent results for ideal cases or for samples modified with a 1% white noise.
Advisor:Claridge, David E.; Culp, Charles H.; Haberl, Jeff S.; Turner, Dan
School:Texas A&M University
School Location:USA - Texas
Source Type:Master's Thesis
Keywords:automated calibration potential energy savings simulated annealing optimization building use simulation
Date of Publication:12/01/2006