Are intelligent agents the key to optimizing building HVAC system performance?

HVAC and R Research

Volumn 18, Issue 4, 2012, Pages 750-759

  Kelly, George E ^a   Bushby, Steven T ^a  

^a NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COST SAVING; HVAC SYSTEM; OPTIMIZATION METHOD; PERFORMANCE OF BUILDINGS; POTENTIAL BENEFITS; RESEARCH EFFORTS; SIMULATION TEST BEDS;

CLIMATE CONTROL; OPTIMIZATION;

INTELLIGENT AGENTS;

EID: 84865203922     PISSN: 10789669     EISSN: None     Source Type: Journal    
DOI: 10.1080/10789669.2012.682693     Document Type: Conference Paper

References (11)

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3. Barr, A., and E.A. Fleigenbaum. 1982. The Handbook of Artificial Intelligence, Volume 2. Stanford, CA: HeurisTech Press.
4. Braun, J.E., S.A. Klein,W.A. Beckman, and J.W.Mitchell. 1989a. Methodologies for optimal control of chilled water systems without storage. ASHRAE Transactions 95(1):652-62.
5. Braun, J.E., S.A. Klein, J.W.Mitchell, andW.A. Beckman. 1989b. Applications of optimal control to chilledwater systemswithout storage. ASHRAE Transactions 95(1):663-75.
6. Cumali, Z. 1988. Global optimization of HVAC system operations in real time. ASHRAE Transactions 94(1):1729-44.
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8. Kelly, G.E., and S.T. Bushby. 2011. Optimization of building HVAC systems using intelligent agents-A proof of concept study. NIST TN 1707, National Institute of Standards and Technology, Gaithersburg, MD.
9. Ljung, L. 1987. System Identification Theory for TheUser. Chapter 1. Englewood Cliffs, NJ: Prentice-Hall, Inc.
10. Pantic, M., R. Zwitserloot, and R.J. Grootjans. 2005. Teaching introductory artificial intelligence using a simple agent framework. IEEE Transactions on Education 48(3):382-90. (Pubitemid 41430905)
11. Pape, F.L.F., J.W. Mitchell, and W.A. Beckman. 1990. Optimal control and fault detection in heating, ventilating, and air-conditioning systems. ASHRAE Transactions 97(1): 729-45.