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  • 學位論文

應用基因演算法於空調系統之最佳運轉

Application of Genetic Algorithm for Air-Conditioning System Optimal Operation

指導教授 : 張永宗
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摘要


雖有許多專家學者提出空調系統之最佳化控制方式,但是僅限於冰水主機或是各附屬設備之個別最佳控制居多。雖然空調箱和泵浦之耗電量不如主機,但是在使用數量上卻是不容忽視的,其耗電量累積起來也相當可觀。目前多數業者採用變頻器並依照使用者之需求調整馬達轉速,來達到節能之目的,但是並無考慮設備與設備之間的關係與特性,故其耗電量並非最低。 環顧過去,針對空調系統運轉最佳化之控制方式大致上可分為:主機最佳負載分配(Optimal Chiller Loading 簡稱OCL)、主機排程最佳化(Optimal Chiller Scheduling 簡稱OCS)與最佳冰水出水溫度等三大類。無論利用何種演算法來達到節能目的,都只針對主機本身做最佳化之控制,故本研究係將冰水主機、空調箱與區域泵浦作結合,再搭配基因演算法(Genetic Algorithm 簡稱GA)中「物競天擇」之理論且在不違反其限制條件下,求取空調系統最佳冰水出水溫、空調箱送風量以及區域泵浦之水流量,透過本研究期望找出在不同環境下空調系統最佳運轉參數之設定方式,使整體設備效益提升以節約用電。

並列摘要


Though many experts have proposed a range of air-conditioning optimization control methods, they are restricted to optimization of the chiller or affiliated units. The air handing unit and pump do not consume as much power as the chiller; however, the accumulated volume of power consumption can not be overlooked. Currently, most manufacturers use inverters to achieve power-saving through adjusting the speed of the motor, but the interrelationships between units and their attributes have not been taken into consideration. Hence, the lowest power consumption is not achieved. In the past researches, control methods for air-conditioning system operation optimization can be classified into three categories: Optimal Chiller Loading (OCL), Optimal Chiller Scheduling (OCS), and Optimal Chilled Water Supply Temperature. No matter which algorithm is used to achieve the purpose of reducing power consumption, most researches targeted only on optimizing control of the chiller. Therefore, this research combines the factors of the chiller, air handing unit, and district pump to derive the optimal chilled water temperature, supply air flow of the air handing unit, and water flow of the district pump through the “natural selection” theory of Genetic Algorithm (GA) without violating the operation constraints. Through this research, we expect to find the optimal operation parameters setting methods for air-conditioning systems under various environments to achieve overall facility efficiency and reduction of power consumption.

參考文獻


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被引用紀錄


杜建甫(2014)。利用模擬退火法與和弦搜尋法比較中央空調之最佳負載分配〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://doi.org/10.6841/NTUT.2014.00045
何承懌(2010)。基於類神經網路耗電模式之基因演算法最佳負載分配〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0006-2607201016082500
黃郁勝(2010)。應用粒子族群演算法於空調冰水系統最佳化運轉之研究〔碩士論文,國立臺北科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0006-2607201014362100

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