Supervisory Control for Energy Savings and Thermal Comfort in Commercial Building HVAC Systems

Information Refinement and Revision for Decision Making: Modeling for Diagnostics, Prognostics, and Prediction

Volume

Papers from the 2002 AAAI Spring Symposium

Contents

The operation and maintenance of commercial building HVAC (heating, ventilation, and air-conditioning) systems is illustrative of an industry that can benefit from the insightful use of all available information sources. Modern HVAC systems using direct digital control can potentially provide useful performance data. Occupant feedback complaint data and HVAC system trend data are stored within modern maintenance management databases. This paper will address the specific issue of integration and application of these fundamental sources of information, using some modern and novel techniques. Examples are found in, but are not limited to the following areas: discrete-event, continuous, and hybrid control system theory, artificial intelligence, statistics, system identification, databases, etc. Methods specific to these areas can be used to synthesize a supervisory controller. The objective of this controller is to reduce energy costs, improve building occupant comfort, fault detection and diagnostic capability. At the same time, the entire process needs to be stable, and the influence of occupant behavior needs to be taken full advantage of. The controller will achieve these objectives by performing and/or prioritizing the appropriate actions to be taken either automatically or by facility operators. Furthermore, the cost and scalability of the entire effort described can be positively influenced by recent technological advances in computing power, sensors, and databases.