應用關聯法則於冰水主機與冷卻水塔系統耗能分析

Analysis of Energy Consumption of Chiller and Cooling Tower System Using Association Rule

周彥騏(Yen-Chi Chou)

指導教授 ： 李文興

國立臺北科技大學/機電學院/能源與冷凍空調工程系碩士班/碩士(2014年)

摘要

現今空調系統中，業界多以經驗多於依據調整水塔風扇，造成在不適當的負載模式下產生了多餘的能源耗費，因此在參數設定上是極為重要的。
資料探勘為一種利用資料庫進行分析之方法，藉著大量資料中，萃取出隱含、過去不為人所知且可信與有效的知識。也可以說是依照使用者所設定的參數，在一群未經處理的資料中找到使用者感興趣的資訊，經過資料的轉化、處理後，提供做為決策者判斷的參考依據。
本文擬利用資料探勘-關聯法則方法對大樓建築物用電資料庫進行分析，藉由建立最小支持度及最小信心度以得到較適合大樓建築物冰水主機及冷卻水塔系統耗能與趨近溫度的操作方式。

關鍵字

關聯法則 ； 冰水主機 ； 冷卻水塔 ； 資料探勘

並列摘要

Today air conditioning system, the control method of the chiller and cooling tower water cooling towers mostly fixed fan speed or with the drive to achieve different operating modes. The most common operation modes is fixed approach temperature or depend on the temperature of cooling tower water to control the cooling tower fan speed. Many manufacturers cannot make the correct parameter settings under different load patterns, often with experience as a basis for setting the parameters. Therefore, parameters on energy consumption have become an important objective of this study.
Data mining is a method of use of database analysis performed. Through large amounts of data, and extract the hidden past is not known but credible and effective knowledge. On the other hand, according to the parameters set by the user, to find information of interest to the user from data in a group of unprocessed. The data is provided for decision-makers to reference for judgment as a basis after data transformation and post-processing. This paper intends to use data mining - association rule approach to building electricity database for analysis. With the establishment of minimum support and minimum confidence level, we can get the most suitable energy and the approach temperature of operation for chiller and cooling tower systems in buildings.

並列關鍵字

Association Rule ； Chiller ； Cooling Tower ； Data Mining

參考文獻

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