ML-11-034 -- A Plug-and-Play Framework for an HVAC Air-Conditioning Unit and Temperature Sensor Auto Recognition Technique—Part I: Review of Critical Technologies ✓ Most Recent

A huge barrier to wider adoption of building automation systems (BAS) in commercial buildings is their complex, timeconsuming, and often proprietary installation, configuration, and commissioning process. A framework for plug-and-play HVAC air-handling unit (AHU) control systems is proposed in this study. This is the foundation and the first step toward a plug-and-play HVAC control system that will eventually lead to self-configuring HVAC control systems for automatic BAS setup, configuration, commissioning, and possible automatic detection and repair of potential controls problems. This framework is built on commercially available smart transducers that are compatible with the IEEE 1451 family of standards. To solve the critical issue of resolving system ambiguity, a structural pattern recognition algorithm is developed to automatically recognize temperature sensor locations in an AHU. The algorithm can be a critical part of a plug-and-play or selfconfiguring HVAC control system in establishing a binding list of control system input/output and automated assignment and verification of the binding list. This work consists of two parts. Part I, the present paper, reviews existing technologies and discusses technology gaps for incorporating plug-and-play and self-configuring concepts into HVAC control systems. A plug-and-play framework for an AHU is then proposed. Part II (Zhou and Nelson 2011), a companion paper, develops a structural pattern recognition algorithm to automatically identify AHU temperature sensor locations and a scheme to resolve AHU system ambiguity. A prototype of the plug-and-play framework for an AHU was built and tested in an experimental facility. Tests are conducted at various initial conditions, environmental temperatures, and chilled-water system configurations to demonstrate the feasibility of the framework and the robustness of the pattern recognition algorithm. See more