Developing and Testing Dynamic Models for HVAC Systems Using System Identification Approach

Abstract

This paper proposes integrated modeling and optimization methods for a chilled water HVAC system using a system identification approach. Two multiple input-single output models are developed to find the supply air temperature and fan power of the investigated chilled water air handling unit AHU. To test the proposed models, actual data are collected from existing HVAC systems. Different fan and cooling coil model structures with various time delays and orders are tested to find the optimal model structure in term of normalized root-mean-square deviation or Coefficient Of Variances (COV). The paper also proposes an optimization procedure integrated into system identification model to automate the process of finding optimal fan and cooling coil model structures yielding the best accurate predictions. The testing results show that the proposed methods can provide accurate predictions that can used for several applications such as control optimization, energy assessment and fault detection and diagnosis.