應用模擬退火演算法於冰水主機負載分配之最佳化

Optimal Chiller Loading Using Simulated Annealing

江建樺(Chien-Hua Chiang)

指導教授 ： 張永宗

國立臺北科技大學/機電學院/冷凍空調工程系所/碩士(2005年)

https://doi.org/10.6841/NTUT.2005.00040

摘要

冰水主機負載分配最佳化之目的在滿足系統負載需求條件下，決定每台冰水主機運轉之最佳負載率，使系統總耗電量達到最小。目前冰水主機的負載分配法有平均負載法、拉格蘭傑法、基因演算法，這些方法皆有其缺點。例如平均負載法並不是最佳運轉點、拉格蘭傑法λ值初值設定不當會有發散的問題、基因演算法程式撰寫過於複雜。為解決上述缺點本文提出模擬退火演算法，它是一種結構簡單、所需記憶空間小、隨機性的演算法，無論目標函數是否連續、可微分，皆能適用。本文以三次多項式來表現冰水主機之kW-PLR性能曲線，並以系統總耗電為目標函數，並在相關限制條件及滿足系統負荷需求下，應用模擬退火演算法進行冰水主機負載分配最佳化使系統總耗電量為最小。

關鍵字

負載分配最佳化 ； 平均負載法 ； 拉格蘭傑法 ； 基因演算法 ； 模擬退火演算法

並列摘要

The purpose of the Optimal Chiller Loading (OCL) is to meet the system load and to decide the chillers’ optimal part load ratios (PLR) to reduce the system power consumption. The optimal chiller loading methods include Average Loading (AVL) method, Largrangian Multiplier (LGM) method and Genetic Algorithm (GA) at present. These methods have some shortcomings. Such as AVL method being not optimal. LGM method will diverge if the initial condition isn’t suitable. GA procedure is complicated. In this paper, Simulated Annealing (SA) can overcome the above-mentioned shortcomings. It is a simple structure with the random algorithm consuming small memory space. Whether the objective function is continuous and differentiable or not, the SA algorithm is still applicable. This thesis use a cubic equation to simulate the chiller’s curve and to find a set of chiller output which doesn’t violate the operating limits while minimizing the objective function. The Simulated Annealing (SA) is adopted to find the near optimal solution of the function.

並列關鍵字

Optimal Chiller Loading ； Average Loading ； Lagrangian Multiplier Method ； Genetic Algorithm ； Simulated Annealing

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