基於ASHRAE準則14之冰水機群組操作最佳化解析解

Analytical Solution of Chillers Operation Optimization Based on ASHRAE Guideline 14

莊博森(Bo-Sen Chuang)

指導教授 ： 劉佩玲

國立臺灣大學/工學院/應用力學研究所/碩士(2020年)

https://doi.org/10.6342/NTU202003089

摘要

台灣缺少自產能源，能源依賴進口，提高能源效率為重要議題。而根據統計，辦公大樓空調耗電約占整體耗電的51%，其中又以冰水機耗電占空調耗電之大宗，因此找出冰水機的最佳操作方法可有效減少冰水機的耗電。冰水機的操作優化可以由開機排序與負載分配著手，本研究之目的即在建立一個同時考慮開機排序與負載分配之冰水機最佳操作方法。
本研究最佳化之目標函數為冰水機總耗電量，並以冰水機的負載上下限與各冰水機的負載總和須等於冷卻負載需求為限制條件，各冰水機之能耗係採用ASHRAE準則14所建議之Gordon-Ng冰水機簡單熱力學模型。由Gordon-Ng模型可發現，各冰水機的耗電量為其冷卻負載之線性函數，而線性函數之係數與冰水出水溫度和冷卻水進水溫度有關。在已知有N台冰水機開啟的情況下，本研究證明，各冰水機之最佳負載一定有N-1台冰水機之負載率為上限或下限，且可依一標準步驟找出最佳化解析解。若排序也同時要最佳化，可將可能的排序一一列出，再以上述方法分別求出各別排序的最佳負載，經比較後找出耗電最小者，即可找出最佳排序與最佳負載。本研究亦建立一套可以快速有效的找出最佳排序的方法。
若要對針對隔日冰水機最佳操作提出建議，除了需針對冷卻負載進行預測，也需對冷卻水回水溫度進行預測，以建立Gordon-Ng模型。從預測的結果可以發現，本研究嘗試的預測模型以向量支援迴歸模型的效果較佳。
本研究以台北市政府大樓之冷凍空調歷史數據建立各冰水機之Gordon-Ng模型，並進行冰水機操作最佳化。結果顯示，本研究所發展之最佳化方法確能有效降低冰水機耗電量。值得注意的是，在冰水設定溫度固定的情況下，各冰水機的冷卻水回水溫度差異不大，導致線性目標函數中各冰水機負載的係數相近，因此負載分配對耗電量的影響不大，相較之下冰水機的排序對耗電量有絕對性的影響。為提升本方法之泛用性及降低計算量，可考慮只對冰水機排序進行最佳化，即可達到有效節能的效果。

關鍵字

ASHRAE準則14 ； Gordon-Ng冰水機簡單熱力學模型 ； 冷卻水進水溫度 ； 冰水機負載分配 ； 冰水機排序 ； 冰水機操作最佳化

並列摘要

In Taiwan, there is a shortage of self-produced energy and is highly dependent on imported energy, so improving energy efficiency is an important issue. According to statistics, the ratio of the power consumption of the heating, ventilation, and air conditioning (HVAC) systems is about 51 % in office buildings, and chillers account for the most power consumption in HVAC systems. Therefore, optimizing the operation of chillers is can help to reduce the power consumption of HVAC systems. The purpose of this study is to establish a method to optimize chillers operation, including chiller sequencing and load distribution.
To achieve this aim, a constrained optimization problem is formulated using the total power consumption of chillers as the objective function. Each chiller load ratio has upper and lower bounds, and the summation of the refrigerating outputs must equal the total cooling load. To calculate the power consumption of each chiller, the Gordon-Ng simplified model, suggested by ASHRAE guideline 14, is adopted to estimate the chiller efficiency. With this model, the power consumption is a linear function of the refrigerating outputs. It can be proved that as N chillers are turned on, the optimal loading distribution occurs as the load ratios of N-1 chillers take the extreme values.
If the chiller sequence also needs to be optimized, we can determine the optimal load distributions for all possible chiller sequences and compare their power consumption. The sequence that requires minimal energy consumption is the optimal chiller sequencing. This study also developed an efficient method to find the optimal chiller sequence. The optimal chiller sequence plus the optimal load distribution as obtained above yields the optimal operation of the chillers.
To determine the optimal chiller operation for the following day, it is needed to predict the cooling water return temperature, appearing in the Gordon-Ng simplified model, and the total cooling load. This research also compared several prediction models. It turned out that the support vector regression gave the best results.
This study used the historical data of the HVAC system in the Taipei City Hall to build the Gordon-Ng simplified models of the chillers. Then, the optimal chiller operations were obtained using the aforementioned method. The result shows that the proposed method is effective in the reduction of power consumption. It is worth noting that if all the chillers have the same chilled water setting temperature and the cooling water return temperature, one can show that the load distribution has no effect on the total power consumption. Even when the cooling water return temperatures of the chillers are close, which is often the case, the chiller sequencing dominates the optimization results. To simplify the chiller control, one may optimize chiller sequencing only and let the system allocate the cooling load in its own way.

並列關鍵字

ASHRAE Guideline 14 ； Gordon-Ng simplified model ； cooling water return temperature ； Chiller loading distribution ； Chiller sequencing ； Chiller Operation Optimization

參考文獻

財團法人台灣綠色生產力基金會，2019，2019非生產性質行業能源查核年報

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