Scalable scheduling of building control systems for peak demand reduction

Proceedings of the American Control Conference

Volumn , Issue , 2012, Pages 3050-3055

  Nghiem, Truong X ^a   Behl, Madhur ^a   Mangharam, Rahul ^a   Pappas, George J ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONTROL SYSTEMS; LARGE SCALE SYSTEMS; SCHEDULING;

BUILDING CONTROL SYSTEMS; CLIMATE CONDITION; ELECTRICITY CUSTOMERS; INTER-DEPENDENCIES; PERIODIC SCHEDULE; SCHEDULABILITY CONDITIONS; SERVICE DISRUPTIONS; SIMULATION EXAMPLE;

AIR CONDITIONING;

EID: 84869383101     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/acc.2012.6315252     Document Type: Conference Paper

References (15)

1. H. Hermanns and H. Wiechmann, "Future design challenges for electric energy supply," in Proc. IEEE Conf. Emerging Technologies & Factory Automation ETFA 2009, 2009, pp. 1-8.
2. M. H. Albadi and E. F. El-Saadany, "Demand response in electricity markets: An overview," in Proc. IEEE Power Engineering Society General Meeting, 2007, pp. 1-5.
3. TRFund Study, "Understanding PECO's general service tariff," 2007.
4. S. Kiliccote, M. Piette, and D. Hansen, "Advanced controls and communications for demand response and energy efficiency in commercial buildings," in Carnegie Mellon Conf. Elec. Power Sys., 2006.
5. K. ho Lee and J. E. Braun, "Development of methods for determining demand-limiting setpoint trajectories in buildings using short-term measurements," Building and Environment, vol. 43, no. 10, pp. 1755-1768, 2008.
6. Y. Ma, F. Borrelli, B. Hencey, B. Coffey, S. Bengea, and P. Haves, "Model predictive control for the operation of building cooling systems," in Proc. ACC'10, 2010, pp. 5106-5111.
7. F. Oldewurtel, A. Ulbig, A. Parisio, G. Andersson, and M. Morari, "Reducing peak electricity demand in building climate control using real-time pricing and model predictive control," in Proc. IEEE CDC'10, 2010, pp. 1927-1932.
8. J. W. S. Liu, Real-time Systems. Prentice Hall, 2000.
9. A. Cervin and J. Eker, "The control server: A computational model for real-time control tasks," in Proc. ECRTS '03, July 2003, pp. 113-120.
10. R. Chandra, X. Liu, and L. Sha, "On the scheduling of flexible and reliable real-time control systems," Real-Time Systems, vol. 24, pp. 153-169, March 2003.
11. R. I. Davis and A. Burn, "A survey of hard real-time scheduling algorithms and schedulability analysis techniques for multiprocessor systems," University of York, Tech. Rep., 2009.
12. M. D. Vedova, M. Ruggeri, and T. Facchinetti, "On real-time physical systems," in Proc. RTNS'10, 2010, pp. 41-49.
13. T. Facchinetti, E. Bibi, and M. Bertogna, "Reducing the peak power through real-time scheduling techniques in cyber-physical energy systems," in First International Workshop on Energy Aware Design and Analysis of Cyber Physical Systems, 2010.
14. T. X. Nghiem, M. Behl, R. Mangharam, and G. J. Pappas, "Green scheduling of control systems for peak demand reduction," in IEEE Conference on Decision and Control (CDC 2011), December 2011.
15. W. J. Rugh, Linear System Theory, 2nd ed. Upper Saddle River, NJ, USA: Prentice-Hall, Inc., 1996.