Evaluation of Chiller Power Consumption Using Grey Prediction
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.
[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.
[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.
@article{"International Journal of Information, Control and Computer Sciences:57824", author = "Tien-Shun Chan and Yung-Chung Chang and Cheng-Yu Chu and Wen-Hui Chen and Yuan-Lin Chen and Shun-Chong
Wang and Chang-Chun Wang", title = "Evaluation of Chiller Power Consumption Using Grey Prediction", abstract = "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 = "Gery system theory, grey prediction, chller.", volume = "3", number = "5", pages = "1348-6", }