GM(1,1)應用於用電趨勢之研究-以某科技大學為例

An Application of GM(1,1) on The Trend of Energy Consumption - An Example of An University of Technology

呂茂亨(Mao-Heng Lu)

指導教授 ： 龔昶元

朝陽科技大學/管理學院/企業管理系/碩士(2010年)

摘要

近幾年來，由於氣候劇烈改變、能源的缺乏，京都議定書簽定後，各國家積極提倡節能減碳，環保意識抬頭促使國人意識到「環保節能」已經是無法避免的趨勢及責任，再生能源使用與減少能源浪費，降低能源對環境衝擊，為目前國際上積極推動之目標。因此，對於學校而言，如何有效避免電能上的浪費，是學校目前ㄧ項重要課題。本文根據某科技大學自2006～2009年之用電量，應用灰色預測理論GM（1,1）模型，預測2010～2013年之用電趨勢，並將研究結果提供予校方做為未來用電政策及環保節能規劃之參考。
　　獲得研究結論為：2010～2013年某科技大學的用電量呈逐年緩慢成長接近零成長之趨勢。由實證分析中得知，本文採用GM（1,1）的預測模型，對某科技大學的用電量進行預測，預測結果的精確度平均達90%以上，符合灰色理論強調少數據小樣本的預測特性，本研究也證明灰色預測模型對於用電量預測之適用性，僅需4筆資料，即可獲得良好之預測結果。

關鍵字

灰色預測理論 ； 環保節能 ； 用電趨勢 ； GM（1.1）

並列摘要

Recently, many nations have been actively promoting energy conservation and carbon reduction after the Kyoto Protocol has been signed and ratified because of the severe climate changes and the depletion of energy resources. The rise of environmental consciousness made Taiwanese people more and more aware of that environmental conservation is an inescapable trend and responsibility to us. The international goal is to diminish the impact of energy consumption on the environment by using renewable energy and by reducing energy overuse. Therefore, how to effectively avoid the over-consumption of energy becomes an important issue for educational institutes. This study has used the energy consumption data from 2006 to 2009 from a technological university and adopted the grey prediction theory GM (1,1) model to forecast electricity consumption for 2010-2013. The results from this research can serve as a reference for educational institutes for future electricity consumption policies and other environmental conservation schemes.
The findings have indicated that the growth of electricity consumption of the technological university for 2010-2013 will decline gradually, and will reach zero growth eventually. In the empirical analysis, GM (1,1) prediction model was employed to forecast the electricity consumption of the technological university. The accurate degree for the prediction results reached 90%, which is consistent with the property of grey theory that emphasizes less data and a small sample size. This research also demonstrated the applicability of grey prediction model on electricity usage forecast, as only four sets of data are required to obtain appropriate prediction results.

並列關鍵字

environmental protection and energy conservation ； grey prediction theory ； GM (1. 1) ； electricity consumption trend

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