冰水主機與冷卻水塔群組最佳化運轉策略研究

Abstract

空調系統主要之功用是提供人類生活或業界生產線合適的環境條件，其應用範圍包括醫院、辦公大樓、學校、公寓及科技產業中的半導體廠等，在工業發展迅速的現代化社會中扮演著重要的角色。在整體建築物之電力負載中以中央空調系統用電所佔的比例最高，其中冰水主機為空調系統主要之耗電來源。由於今日能源問題日益嚴重，如何有效節約冰水主機的用電量成為各界主要研究的課題。 本研究中首先建立冰水主機及冷卻水塔之耗能計算方程式，經由該方程式提出三套不同操作策略下，冰水主機與冷卻水塔聯合運轉之耗電計算模式，藉由該模式可分別模擬冰水主機與冷卻水塔在各種不同操作策略下聯合運轉時，其系統之耗電量以及該系統在各種不同運轉條件下之最佳化運轉操作點。最後以最佳化之計算模式為基礎，結合懲罰函數法以及節能關機策略建立冰水主機與冷卻水塔群組最佳化節能運轉策略之計算模式。藉由該模式可求得各台冰水主機最佳化負載分配之情形以及空調系統最佳化節能運轉之操作點，同時由該模式亦可模擬空調系統中，冰水主機與冷卻水塔群組於各運轉操作條件下最佳化之耗電情形。 由本研究之結果可知，單台冰水主機與冷卻水塔運轉於最佳化操作點時，可較其它控制策略節省系統總耗電量達1.44%~6.3%。此外在冰水主機與冷卻水塔群組聯合運轉時，若系統以懲罰函數法以及節能關機策略進行負載分配，則空調空間之負載在30%時，可有效節約空調系統總耗電量高達27.86%。

This thesis presents two methodologies for determining the optimal control settings of condenser water system of chiller water plant. One is applied to the system operated with single chiller and cooling tower, and the other is utilized to the system with multiple chillers and cooling towers. By using these methodologies, the power consumption of the system can be minimized. In this research, a mathematical model was developed to predict the power requirement of a chiller under the cooling capacity varied through time, and the water temperature at the time entering condenser and leaving evaporator. Another mathematical model was developed to predict the power requirement of a cooling tower with various ambient conditions, tower air flow rates, tower inlet and outlet water temperatures. By integrating those models, this thesis develop an algorithm for investigating optimal control settings of the system consisted of single chiller and cooling tower, those settings changes through time in respond to uncontrolled variables such as the ambient conditions and the system cooling loads. In a multiple-chiller system, an optimization methodology was developed by integrating the Penalty Function Method (PFM) into the algorithm developed before, where PFM was applied to optimize chiller load distribution. Besides, a strategy was added to save energy. The strategy was utilized to shut down the chillers which operate inefficiently in order to let the rest of the on-line chillers to operate more efficiently and to reduce the energy consumption as well. Results of this optimization methodology are compared with the methodology integrated with Equal Load Distribution Method (ELDM). The results show that the PFM can save 1.7~8.8% total power compared with ELDM while the system load is 60~70%. When the system cooling load is 30%, PFM saved 27.86% total power consumption of multiple chillers and cooling towers in the system.