Energy Analysis for Air Conditioning System Using Fuzzy Logic Controller
Abstract
Reducing energy consumption and to ensure thermal comfort are two important considerations for the designing an air conditioning system. An alternative approach to reduce energy consumption proposed in this study is to use a variable speed compressor. The control strategy will be proposed using the fuzzy logic controller (FLC). FLC was developed to imitate the performance of human expert operators by encoding their knowledge in the form of linguistic rules. The system is installed on a thermal environmental room with a data acquisition system to monitor the temperature of the room, coefficient of performance (COP), energy consumption and energy saving. The measurements taken during the two hour experimental periods at 5-minutes interval times for temperature setpoints of 20oC, 22oC and 24oC with internal heat loads 0, 500, 700 and 1000 W. The experimental results indicate that the proposed technique can save energy in comparison with On/Off and proportional-integral-derivative (PID) control.
Full Text:
PDFReferences
Nasution H. Energy Analysis of An Air Conditioning System Using PID and Fuzzy Logic Controllers. Thesis. Johor Bahru: Faculty of Mechanical Engineering UTM; 2006.
Nasution H, Wan Hassan MN. Saving Energy for Air Conditioning With Variable Speed and Proportional Control System. Proceeding of the Malaysia Science and Technology Congress 2003. Kuala Lumpur. 2003a: 843-850.
Nasution H, Wan Hassan MN. Variable Speed Motor of Compressor for Energy Saving of Air Conditioning. Proceeding of the Intl. Conference on Fluid and Thermal Energy Conversion 2003. Bali. 2003b: 053-1-053-9.
Yu PCHA. Study of Energy Use for Ventilation and Air-Conditioning Systems in Hong Kong. Thesis. Hongkong: The Hong Kong Polytechnic University; 2001.
Masjuki HH, Mahlia TMI, Choudhury IA. Potential Electricity Savings by Implementing Minimum Energy Efficiency Standards for Room Air Conditioners in Malaysia. Energy Conversion & Management. 2001; 42: 439-450.
Nasution H, Wan Hassan MN. Energy Saving for Air Conditioning by Proportional Control, Variable and Constant Speed Motor Compressor. Proceeding of the 2nd Intl. Conference on Mechatronics 2005. Kuala Lumpur. 2005: 492-498.
Nasution H. Variable Speed Drives of Reciprocating Compressor for Air Conditioning: Literature Review. Jurnal SAINSTEK. 2003; 6: 25-39.
Hamed B. Comparison of Fuzzy Logic and Classical Controller Design for Nonlinear System, Thesis. Mexico: New Mexico State University; 1999.
Petchers N. Combined Heating, Cooling & Power Handbook: Technologies & Applications. United States of America: Marcel Dekker. 2003.
Perdikaris GA. Computer Controlled Systems Theory and Applications. Netherlands: Kluwer Academic Publisher. 1991.
Pasino KM, Yurkovich S. Fuzzy Control. United State of America: Addison Wesley. 1998.
Nasution H. Development of Fuzzy Logic Control for Vehicle Air Conditioning System. TELKOMNIKA. 2008; 6(2): 73-82.
Dounis AI, Manolakis DE. Design of A Fuzzy System for Living Space Thermal Comfort Regulation. Applied Energy. 2001; 69: 119-144.
Hussu A. Fuzzy Control and Defuzzification. Mechatronics. 1995: 5. 513-526.
Yasin SY. Systematic Methods for the Design of A Class of Fuzzy Logic Controllers. Thesis. Michigan: Western Michigan University; 2002.
Chen Z. Consensus in Group Decision Making Under Linguistic Assessments. Thesis. Kansas: Kansas State University; 2005.
Eker I, Torun Y. Fuzzy Logic Control to be Conventional Method. Energy Conversion & Management. 2006; 47: 377-394.
Bagis A. Determining Fuzzy Membership Functions With Tabu Search-An Application to Control. Fuzzy Sets and Systems. 2003; 139: 209-225.
Gayakwad R. Optimized Fuzzy Logic for Motion Control. Acta Polytechnica Hungarica. 2010; 7(5): 161-168.
Murtha J. Applications of Fuzzy Logic in Operational Meteorology. Scientific Services and Professional Development Newsletter, Canadian Forces Weather Service. 1995; 42-54.
Kushwana GS, Kumar S. Role of the Fuzzy System in Psychological Research. Europe’s Journal of Psychology. 2009; 2:123-134.
Pedrycz W. Why Triangular Membership Functions?. Fuzzy Sets and Systems. 1994; 64: 21-30.
Kolokotsa D, Tsiavos D, Stavrakakis GS, Kalaitzakis K, Antonidakis E. Advanced Fuzzy Logic Controllers Design and Evaluation for Buildings’ Occupants Thermal Visual Comfort and Indoor Air Quality Satisfaction. Energy and Buildings. 2001; 33: 531-543.
DOI: http://doi.org/10.12928/telkomnika.v9i1.680
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120
Fax: +62 274 564604