%0 Journal Article %A 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 %D 2009 %J International Journal of Computer and Information Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 29, 2009 %T Evaluation of Chiller Power Consumption Using Grey Prediction %U https://publications.waset.org/pdf/8750 %V 29 %X 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. %P 1303 - 1308