在能源價格節節攀升的國際情勢下，台灣能源轉型的首要目標即是太陽能源及風能；而評估太陽能資源中所需各種不同類型的太陽輻射量資訊卻在國內尚有所欠缺。由於目前國內氣象站僅觀測全天空輻射量，對於聚焦式太陽能設備所需的直接輻射量與漫輻射量兩類數據並未觀測，數據的缺少導致很難有效的估算各地太陽能資源的可應用性，亦無法利用相關數據來建立參考模型。因此本研究考量台灣本島被眾多山脈所區隔的東西岸與台灣本島周圍分佈的一些小離島的地理特徵，分別在台南歸仁區、澎湖馬公市與台東市設置量測漫射分率的全天空輻射計與漫射儀。所得觀測數據依經典氣象年之篩選方法建立此三地的經典氣象年數據集，並以此數據集開發評估太陽能應用所需的漫射分率模型。本研究以歸仁站十年數據建立經典氣象年數據集，因多變數模型中須使用k_t前後小時之自變數，不利於「即時」預測使用，因此亦建立了「即時」預測之單變數模型，並以此數據集開發多變數模型(分段多變數模型及BRL模型)與單變數模型(分段四階多項式及simple logistic模型)，並與過去使用相同測站(歸仁站)所建立的漫射分率模型進行比較，其結果顯示以經典氣象年數據所建立的漫射分率模型，其性能皆優於過去僅以一年或某一區間所建立的模型；此一結果說明經典氣象年數據可代表該地區的長期氣候特徵，以該數據集所建立的模型也證實其模型預測性能最佳，這對於國際上建立漫射分率模型所使用的數據區間仍未有一致的共識，提供一個新的參考方向。本研究也確認台灣東西岸與離島的漫射分率模型確實存在地區上的差異，所建立不同地區的漫射分率模型建議採本研究所發展之分段多變數模型及分段四階多項式單變數模型，將可應用於國內此三種不同地形上的漫射分率。

This study considered the geographical features of the east and west coasts of Taiwan's main island separated by five north – south bound mountain ranges. Also, Taiwan's main island has some small and large outlying islets around its perimeter. Thus, a pyranometer with a shadow band was separately set up for measuring the diffuse fraction at the Guiren station located in Tainan, Magong station located in Penghu County and the station located in Taitung City. The observational data were used to establish the datasets of these three locations based on the method of typical meteorological year (TMY). The datasets were used to develop the diffuse fraction model which were necessary to assess the solar energy resources.

Furthermore, the TMY dataset for the Guiren station was established based on the data collected over a ten-year period. The dataset was also used to develop the multiple and single variable models which were then compared with the diffuse fraction model established in the past by using the same station (Guiren). The results showed that the diffuse fraction models based on the TMY data were all found to be better than those of the previous models based only on one year or a certain interval period.

This clearly showed that the TMY data could represent the long-term climate characteristics of a given location and thus it was suggested that the model established with this dataset showed the best predictive performance. This could indeed provide a new reference direction for the lack of consensus on the data interval used to establish the diffuse fraction model internationally.

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