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Evaluation of Chiller Power Consumption Using Grey Prediction

Authors: Tien-Shun Chan, Yung-Chung Chang, Cheng-Yu Chu, Wen-Hui Chen, Yuan-Lin Chen, Shun-Chong Wang, Chang-Chun Wang


98% of the energy needed in Taiwan has been imported. The prices of petroleum and electricity have been increasing. In addition, facility capacity, amount of electricity generation, amount of electricity consumption and number of Taiwan Power Company customers have continued to increase. For these reasons energy conservation has become an important topic. In the past linear regression was used to establish the power consumption models for chillers. In this study, grey prediction is used to evaluate the power consumption of a chiller so as to lower the total power consumption at peak-load (so that the relevant power providers do not need to keep on increasing their power generation capacity and facility capacity). In grey prediction, only several numerical values (at least four numerical values) are needed to establish the power consumption models for chillers. If PLR, the temperatures of supply chilled-water and return chilled-water, and the temperatures of supply cooling-water and return cooling-water are taken into consideration, quite accurate results (with the accuracy close to 99% for short-term predictions) may be obtained. Through such methods, we can predict whether the power consumption at peak-load will exceed the contract power capacity signed by the corresponding entity and Taiwan Power Company. If the power consumption at peak-load exceeds the power demand, the temperature of the supply chilled-water may be adjusted so as to reduce the PLR and hence lower the power consumption.

Keywords: Grey prediction, Gery system theory, chller

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[1] Hittle DC.,"The building loads analysis and system thermodynamics program (BLAST)" US Army Construction Engineering Research Laboratory (CERL). Champaign, IL, 1977.
[2] Stoecker WS, Jones JW, Refrigeration and Air Conditioning, USA: McGraw-Hill, 1982.
[3] Strand RK, Pederson CO, Coleman GN., "Development of direct and indirect ice-storage models for energy analysis calculations," ASHRAE Trans 1994, 100(1):1230-44.
[4] Babak Solati, Radu Zmeureanu , Fariborz Haghighat.," Correlation based models for the simulation of energy performance of screw chillers," Energy Conversion and Management, vol.44, 2003, pp. 1903-1920.
[5] C.L. Chen, "Optimal operation of Chiller and Cooling tower for semiconductor Factory," M.S. thesis, Dept. ERA Eng., Taipei Univ., Taipei, Taiwan, 2004.
[6] K.T.Chan, F.W.Yu ,"Optimum Setpoint of Condensing Temperature for Air-Cooled Chillers,"HVAC&R RESEARCH ", vol. 10, no. 2,2004, pp. 113-128.
[7] P.W. Tai, "Verification Approach for Chillers Applied to Energy Saving Performance Contract," M.S. thesis, Dept. ERA Eng., Taipei Univ., Taipei, Taiwan, 2006.
[8] H.C. Lan , "The Study of Thermal Comfort and Saving Energy on HVAC Using Gray Prediction with Fuzzy Control," M.S. thesis, Dept. Industrial Edu., Changhua Univ., Changhua City, Taiwan, 2001.
[9] Yiqiang Jiang, Yang Yao, Shiming Deng, Zuiliang Ma, "Applying grey forecasting to predicting the operating energy performance of air cooled water chillers," International Journal of Refrigeration, vol.27, 2004, pp. 385-392.
[10] Y.C. Li, "The Discharge Performance Analysis of Ice Storage Systems by Adopting Gray Theory Prediction," M.S. thesis, Dept. Auto&Control., Taiwan Univ., Taipei, Taiwan, 2005.
[11] J. L. Deng, "Control Problem of Grey System," Systems and Control Letter, Vol. 1, No. 5, 1982.
[12] J. L. Deng. And H. Kuo, Principle and Application of Grey Predict. Chuan Hwa Book CO,1996, pp374-375.