旅館業之耗能因子及負載預測分析

The Analysis of Energy Consumption Factors and Load Prediction for Hotel Industry

賴宗文(Tsung-Wen Lai)

指導教授 ： 陳文輝

國立臺北科技大學/機電學院/自動化科技研究所/碩士(2008年)

https://doi.org/10.6841/NTUT.2008.00048

摘要

本文以觀光旅館業為例，利用複迴歸分析及灰色理論進行電力耗能因子評估與負載預測分析。使業者在促進地方觀光產業之外，也能有效使用能源，達到節約能源之目的。由於觀光旅館為一具多功能性之公共場所，因此對於負載變動有很大影響之外氣溫度及設備場所使用率就難以掌握，如此將增加負載預測之困難度及複雜性。為解決這些問題，在深入探討分析觀光旅館業之組織架構、空間區劃以及營運方式之後，我們藉由耗能影響因子分析，找出主要影響能源消耗之主要因子及其影響程度後，以灰預測模型作負載預測之主要方法。實驗數據顯示其整體平均誤差，在不同年但相同月份的情況下，可以獲得1.95% 之準確度。顯見本文所建立之負載預測模型，可提供觀光旅館業者作為能源管理及規劃之依據，達到節約能源，提高設備營運效率之目標。

關鍵字

複迴歸分析 ； 灰關聯分析 ； 灰預測 ； 耗能指標 ； 耗能影響因子

並列摘要

This article is to take tourist hotel industry as an example, adopting the multiple regression analysis and the grey theory to conduct the electrical energy consumption factors evaluation and the load prediction analysis. The objective is to urge the hoteliers besides promoting the local tourist industry, also to consume the energy with efficiency as well as to conserve the energy. As tourist hotels are multi functional public place, the major influencing factors to the load variable, such as outside temperature and the utility rate of the facilities and place, are quite difficult to control; this will make the load predictions even harder and more complicated. In order to resolve these problems, by taking advanced investigation and analysis of the organization frameworks, the space divisions, and the operation methods of the tourist hotel industries, it is to base on the energy consumption influencing factor analysis to find out the main factor and the degrees of impact that influencing the energy consumption, and to predict the loading by grey prediction model as main method. The experiment data indicated that the overall average error could reach 1.95% accuracy in the same month of different year. It is obvious to see the model of load prediction by this article could offer a foundation for the tourist hotel industries to have better energy management and planning, in order to have better energy conservation and make it more efficient, and to increase the efficiency of operation.

並列關鍵字

Multiple regression model analysis ； grey relational analysis ； grey prediction theory ； energy consumption index ； energy consumption influence factor

參考文獻

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