本研究將拋物面集熱器收集相變化材料(Phase Change Material)儲熱槽結合，太陽能集熱器收集熱能，加熱後的熱油再導入相變化儲存槽中儲能，儲存槽中出口的油再流回至集熱器加熱，如此形成一個循環。本研究所使用之相變化材料儲熱槽採用的是垂直殼管式設計，在每個管中放入相變化材料-木醣醇，木醣醇相變化過程中吸收的潛熱為247.9kJ/kg。因儲存槽內的殼管採蜂巢式設計，本研究利用30-60-90三角柱模型模擬儲熱槽內的熱油與相變化材料之間的熱傳行為，將實驗得到儲熱槽進口油溫導入30-60-90三角柱模型進行模擬，並利用實驗得到儲熱桶溫度計算熱散，最後可以利用模擬預測儲存能量達到實驗值的91%。
另一方面本論文嘗試利用不同於EN12975的測試方法及準動態方程式對拋物面槽式太陽能集熱器進行性能測試，新的動態量測法不使用固定三段入口油溫的方法，改採用入口油溫會持續穩定上升的數據作為回歸用數據，新的動態量測所採用的準動態方程式也與EN12975有所不同，將 除去，並將 移至等式前面變成了 ，公式如下:

，利用以上兩種方法在2017年2月對集熱器進行測試，並回歸得到2月的參數，利用兩種方法得到的參數預測4月的收集功率，結果利用新動態量測法預測的收集功率與實驗值的誤差(NRMSE)只有2%，利用新動態量測法得到的參數具有一定的準確度。

This research stores solar heat energy that collected by Parabolic Trough Collector (PTC) in Phase Change Material Storage tank (PCM storage tank). Vertical shell and tube is adopted as PCM storage tank. The latent heat of PCM-Xylitol is 247.9kJ/kg. Xylitol is filled into copper tubes as PCM tubes. In order to simplify simulation, 30°–60°–90° Triangular prism is used to simulate heat transfer of PCM tube. Three kinds of triangular prism models are developed. Model 1 is that a PCM tube is soaked in oil. Model 2 is that two thermocouple housings are inserted into model 1. Model 3 is a model that full of oil. Entrance boundary conditions of these three models are from experiment. In addition to 3 triangular prism models, heat-loss model is used to calculate heat-loss. As shown in the result, stored energy of model 1 is 69.6kJ, model 2 is 70.5kJ and model 3 is 62.6 kJ. The stored energy of models with PCM tube is higher than model 3. Because of housings, temperature of xylitol in model 2 is always higher than model 1. It is necessary to consider whether the design of the structure will affect the accuracy of temperature measurement before experiments.
On the other side, this study uses the new test method different from EN12975 o test PTC. New method adopts continuously rising oil temperature data for linear regression. The equation for new method:

in EN-12975 is moved to the left of the equation, and becomes . The PTC was tested in Feb,2017 by new method, model of Feb,2017 are obtained in this test. The error between Pcol/A predicted by model and the experimental data is only 2%. The parameter that obtain from new method is able to predict oil Pcol/A.

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