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The Identification and Optimization of the HVAC Partial Subsystems in Intelligent Buildings
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This paper presents on modeling of outside air systems (OAS) and air condition systems (ACS) of intelligent buildings (IB). The open loop identification estimation method is adopted for uncorrelated noises between the input and output (I/O) measurements. Analysis of input variables of these two processes verifies the supply water temperature is a significant factor in certain cases. The Variable Decoupling is proposed during processing the measured data. The M-sequence for water valve actuator during measurements is proved to be authentic by its auto-correlative function calculation. An Instrumental Variable method (IV) is used as consistent estimation. A Determinant Ratio method is used for measured data-based model's order estimation. A set of candidate model structures are used for comparison of their properties. Cross Correslation Function calculation between the residulas and input of obvained model shows theri validation. All modeling results for several P.R.C IBS have proven their correct, efficient and robust features.
Zhao, Z.; Xiong, Y. (2004). The Identification and Optimization of the HVAC Partial Subsystems in Intelligent Buildings. Energy Systems Laboratory (http://esl.tamu.edu); Texas A&M University (http://www.tamu.edu). Available electronically from