Final Project Report: Self-Correcting Controls for VAV System Faults Filter/Fan/Coil and VAV Box Sections

Brambley, Michael R. ; Fernandez, Nicholas ; Wang, Weimin ; Cort, Katherine A. ; Cho, Heejin ; Ngo, Hung ; Goddard, James K.

关键词: AIR CONDITIONING;    ALGORITHMS;    CHAINS;    COMMISSIONING;    ECONOMICS;    HEATING;    METERS;    SENSORS;    SYMPTOMS;    TRAINING;   

DOI  :  10.2172/1032697
RP-ID  :  PNNL-20452
PID  :  OSTI ID: 1032697
Others  :  Other: 600305000
Others  :  TRN: US201202%%401

学科分类：能源（综合）

美国|英语

来源: SciTech Connect

【 摘 要 】

This report addresses original research by the Pacific Northwest National Laboratory for the California Institute for Energy and Environment on self-correcting controls for variable-air-volume (VAV) heating, ventilating and air-conditioning systems and focuses specifically on air handling and VAV box components of the air side of the system. A complete set of faults for these components was compiled and a fault mode analysis performed to understand the detectable symptoms of the faults and the chain of causation. A set of 26 algorithms was developed to facilitate the automatic correction of these faults in typical commercial VAV systems. These algorithms include training tests that are used during commissioning to develop models of normal system operation, passive diagnostics used to detect the symptoms of faults, proactive diagnostics used to diagnose the cause of a fault, and finally fault correction algorithms. Ten of the twenty six algorithms were implemented in a prototype software package that interfaces with a test bed facility at PNNL's Richland, WA, laboratory. Measurement bias faults were instigated in the supply-air temperature sensor and the supply-air flow meter to test the algorithms developed. The algorithms as implemented in the laboratory software correctly detected, diagnosed and corrected these faults. Finally, an economic and impact assessment was performed for the State of California for deployment of self-correcting controls. Assuming 15% HVAC energy savings and a modeled deployment profile, 3.1-5.8 TBu of energy savings are possible by year 15.