Optimal decision making in ventilation control

Energy

Volumn 34, Issue 11, 2009, Pages 1835-1845

  Kusiak, Andrew ^a   Li, Mingyang ^a  

^a UNIVERSITY OF IOWA   (United States)

Author keywords

Air quality; Energy saving; Evolutionary strategy; Multi objective optimization; Scheduling; Ventilation

Indexed keywords

AIR QUALITY; ENERGY CONSERVATION; EVOLUTIONARY ALGORITHMS; INDOOR AIR POLLUTION; VENTILATION;

ENERGY COST; ENERGY SAVING; EVOLUTIONARY STRATEGIES; INDOOR AIR QUALITY; MULTI-OBJECTIVE OPTIMIZATION MODELS; OPTIMAL DECISION MAKING; OPTIMAL SOLUTIONS; SCHEDULING MODELS; TIME HORIZONS; VENTILATION CONTROL;

MULTIOBJECTIVE OPTIMIZATION;

AIR QUALITY; ALGORITHM; CARBON DIOXIDE; DECISION MAKING; ENERGY BUDGET; ENERGY CONSERVATION; INDOOR AIR; MODEL TEST; OPTIMIZATION; VENTILATION;

EID: 77949542289     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2009.07.039     Document Type: Article

References (26)

1. Energy Information Administration. U.S. Household electricity report. Available from: (2005). http://www.eia.doe.gov/emeu/reps/enduse/er01_us.html
2. American Society of Heating, Refrigerating and Air-Conditioning Engineers. ANSI/ASHRAE 90.1-2001, Energy standard for buildings except low-rise residential buildings. SI Edition (2001), American Society of Heating, Refrigerating and Air-Conditioning Engineers, Atlanta
3. American Society of Heating, Refrigerating and Air-Conditioning Engineers. ANSI/ASHRAE 62-2004, Design for acceptable indoor air quality (2004), American Society of Heating, Refrigerating and Air-Conditioning Engineers, Atlanta
4. Mui K.W., and Chan W.T. Building calibration for IAQ management. Building and Environment vol. 41 No.7 (2006) 877-886
5. Capehart B.L. Encyclopedia of energy engineering and technology (2007), CRC Press, Boca Raton, FL
6. 2-based demand-controlled ventilation. ASHRAE Transactions vol. 103 No.2 (1997) 229-243
7. Federspiel C.C. On-demand ventilation control: a new approach to demand-controlled ventilation. Proceedings of INDOOR AIR '96 vol. 3 (1996) 935-940
8. Ke Y.P., and Mumma S.A. Using carbon dioxide measurements to determine occupancy for ventilation controls. ASHRAE Transactions vol. 103 No.2 (1997) 365-374
9. Gouda MM. Fuzzy ventilation control for zone temperature and relative humidity. In: 2005 American Control Conference, p. 507-512, 2005.
10. Ke Y.P., and Mumma S.A. Optimized supply-air temperature in variable-air-volume systems. Energy vol. 22 No. 6 (1997) 601-614
11. Chang Y.C., and Chen W.H. Optimal chilled water temperature calculation of multiple chiller systems using Hopfield neural network for saving energy. Energy vol. 34 No. 4 (2009) 448-456
12. Zheng G.R., and Zaheer-Uddin M. Optimization of thermal processes in a variable air volume HVAC system. Energy vol. 21 No. 5 (1996) 407-420
13. Mossolly M., Ghali K., and Ghaddar N. Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm. Energy vol. 34 No. 1 (2009) 58-66
14. Chang Y.C. An innovative approach for demand side management-optimal chiller loading by simulated annealing. Energy vol. 31 No. 12 (2006) 1883-1896
15. Persily A, Dols WS. The relation of CO2 concentration to office building ventilation ASTM Standard Technical Publication; 1997.
16. Fisk W.J., and De Almeida A.T. Sensor-based demand-controlled ventilation: a review. Energy and Buildings vol. 29 No.1 (1998) 35-45
17. Fisk W.J. Health and productivity gains from better indoor environments and their relationship with building energy efficiency. Annual Review of Energy and the Environment vol. 25 No.1 (2000) 537-566
18. 2 controlled mechanical ventilation systems. Technical Note 12/94.1 (1994), BSRIA, UK
19. Fonseca C.M., and Fleming P.J. An overview of evolutionary algorithms in multiobjective optimization. Evolutionary Computation vol. 3 No.1 (1995) 1-16
20. Syswerda G, Palmucci J. The application of genetic algorithms to resource scheduling. In: Proceedings of the Fourth International Conference on Genetic Algorithms; 1991.
21. Powell D, Skolnick MM. Using genetic algorithms in engineering design optimization with non-linear constraints. In: Proceedings of the Fifth International Conference on Genetic Algorithms; 1993.
22. Goldberg D.E. Genetic algorithms in search, optimization and machine learning (1989), Addison-Wesley,, Boston, MA
23. Deb K. Multi-objective optimization using evolutionary algorithms. 1st ed. (2001), John Wiley, Chichester, England
24. Zitzler E., and Thiele L. Multi-objective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Transactions on Evolutionary Computation vol. 3 No.4 (1999) 257-271
25. Eiben A.E., and Smith J.E. Introduction to evolutionary computing (2003), Springer, Berlin, New York
26. Casella G., and Berger R. Statistical inference. 2nd ed. (1990), Brooks/Cole, Pacific Grove, CA