Application of Grey System Theory to Predict Chiller Power Consumption

碩士 === 國立臺北科技大學 === 能源與冷凍空調工程系碩士班 === 95 === 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 cust...

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Bibliographic Details
Main Authors: Cheng-Yu Chu, 朱正宇
Other Authors: 張永宗
Format: Others
Language:zh-TW
Published: 2007
Online Access:http://ndltd.ncl.edu.tw/handle/7md3dw
Description
Summary:碩士 === 國立臺北科技大學 === 能源與冷凍空調工程系碩士班 === 95 === 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 theory 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 theory, only several numerical values (at least four numerical values) are needed to establish a GM(1,N). If PLR, the temperatures of supply chiller-water and return chiller-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 contract power capacity, the temperature of the supply chiller-water may be adjusted so as to reduce the PLR and hence lower the power consumption.