在台灣地區98 %的能源都必須仰賴國外進口,石油及電費一直存在著漲價的趨勢,台電近年來不論在裝置容量、發電量、售電量及用戶數等都持續成長,因此該如何節省能源是相當重要的課題。為了得知冰水主機電力需求負荷,傳統方式以線性迴歸建立主機耗電模型,而本研究應用灰色理論建立模型,並預測冰水主機的耗電量,以抑制尖峰負載時之電力需求,如此可以減低客戶端與電力公司之間契約容量的成本,對於提供電力的業者而言,亦可以減緩裝置容量不斷增大的趨勢。 利用灰色預測只需要少許數據(最少四筆)就可以進行的優點下,可快速建立主機GM(1,N)模型以便進行預測。將冰水主機運轉數據中的PLR、冰水出入水溫及冷卻水出入水溫等五個影響參數同時考慮時,所得到的預測結果相當準確,與實際耗電量相比,在短期預測上準確率高達99%以上,透過此方法可事先預知主機耗運轉於尖峰負載時的耗電量,是否會超過與電力公司所簽訂的契約容量,以便調整主機冰水出水溫,降低PLR而達到抑制耗電量之目的。
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.