WASET
	@article{(Open Science Index):https://publications.waset.org/pdf/8750,
	  title     = {Evaluation of Chiller Power Consumption Using Grey Prediction},
	  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},
	  country	= {},
	  institution	= {},
	  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.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {3},
	  number    = {5},
	  year      = {2009},
	  pages     = {1303 - 1308},
	  ee        = {https://publications.waset.org/pdf/8750},
	  url   	= {https://publications.waset.org/vol/29},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 29, 2009},
	}