- 學位論文
應用迴歸分析於冰水主機與冷卻水塔系統之最佳化控制策略
Optimal Control Strategy of Chiller and Cooling Tower System Using Regression Analysis
摘要
隨著資訊科技的發展及資料庫建立的普及，企業可以很容易的紀錄每天的用電資訊，經過長年的累積成為龐大的資料，這些資料蘊藏著協助企業訂定節能決策之資訊。如何從大量的資料中篩選出有意義的資料是一大課題。 目前現行的空調系統中，冷卻水塔的控制方式大多是定頻或變頻搭配不同的控制模式，較常見的運轉模式為固定趨近溫度以及固定水塔出水溫度，而許多廠商無法在不同的附載模式下做出正確的參數設定，往往都以經驗做為各項參數的設定依據，因此參數對耗能的影響便成為本研究的重要目的。 本研究首先根據101年新北市某醫院大樓空調用電資料，運用多元迴歸分析後向選取法迴歸出一經驗公式，進一步將資料根據空調負載與外氣濕球溫度分為四類，低負載群、中下負載群、中上負載群及高負載群，再將每一負載群之空調負載及外氣濕球溫度代入迴歸方程式，進而探討在不同空調負載及外氣濕球溫度之最佳冷卻水回水溫度。 由分析結果可得知，當外氣濕球溫度介於20~22℃時，最佳冷卻水回水溫度皆為28℃，當外氣濕球溫度介於23~25℃時，最佳冷卻水回水溫度皆為29℃，當外氣濕球溫度介於26~28℃時，最佳冷卻水回水溫度皆為30℃。
並列摘要
With the popularization of information technology development and the establishment of a database, enterprises can easily record daily electricity information. The information becomes huge data after accumulated for many years. These data store some decisive information for enterprise to set energy-saving decisions. How to filter out meaningful information from large amounts of data is a major issue. The existing air conditioning system, the control of cooling towers is mostly fixed or variable frequency with different control modes. The most common operation mode are fixed approach temperature, and fixed tower water temperature. 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. In this study, the data of air conditioning electricity consumption is based on a hospital building in new Taipei city, 2012. We used backward election from multiple regressions to calculate an empirical formula. According to the air conditioning load and the outside air wet bulb temperature, the information is further divided into four categories, low-load group, low-mid-load group, mid-high-load group, high-load group. Then take each of the air-conditioning loads and outside air wet bulb temperature of load groups into the regression equation. And then explore the best temperature of cooling return water in different air conditioning load and outside air wet bulb temperature. Results from the analysis that, when the outside air wet bulb temperature is between 20 ~ 22 ℃, optimum cooling water return temperature are 28 ℃. When the outside air wet bulb temperature is between 23 ~ 25 ℃, optimum cooling water return temperature are 29 ℃. When the outside air wet bulb temperature is between 26 ~ 28 ℃, optimum cooling water return temperature are 30 ℃.