臺灣博碩士論文加值系統

摘要
題 目 ：建立台灣在經典氣象年中的太陽能資料庫
研 究 生 ：嚴偉倫
指導教授 ：張克勤
　　在日本福島第一核電廠核災後，台灣已經掀起了一波反核能的浪潮，又顧慮火力發電所需燃料大多依賴進口，並且有空氣汙染的問題，故台灣極力發展再生能源，其中由於台灣位於北迴歸線附近，日照時數長，所以太陽光電及太陽光熱的應用在台灣再生能源中扮演著很重要的角色。但在台灣太陽能應用評估的數據上，缺乏漫射率資料，並且中央氣象局在2003年4月以前所裝置之日射量測儀器皆有誤差，故本研究為了更新並補齊台灣太陽能資料庫，使用中央氣象局2004年至2013年十年間全台30個氣象觀測站之氣象資料，將其氣象觀測站缺少資料利用三階方程式進行補齊，並按照經典氣象年的規範與步驟整理出三種加權函數下的經典氣象年，此經典氣象年之氣象資料可代表該地區的常態氣候狀況，且應用在不同的領域可選擇不同之加權函數。往後在評估太陽能應用時可做參考本研究所選取之經典氣象年氣象資料。
　　太陽能輻射量通常可分為兩種形式：直射輻射量與漫射輻射量。而漫射率則為兩者之間的比值，其漫射率直接影響某些太陽能應用之效率，故本研究以2014年國立成功大學歸仁校區量測之漫射率資料進行內差補齊並刪去不符合物理意義之量測值，最後迴歸成一條三階經驗方程式， 以利於往後在台灣預估漫射率時可以使用。

Establishment of Taiwan solar energy information
in terms of the typical meteorological year

Author: Yen Wei-Lun
Advisor: Chang Keh-Chin

Department of Aeronautics and Astronautics, National Cheng Kung University
SUMMARY
Taiwan is located in the subtropics with abundant solar irradiation. So, solar energy is the most available green energy for Taiwan. Thus, Taiwan is suitable for developing solar energy applications. The solar irradiation database of Taiwan is incomplete, and the instruments for the measurements of global-radiation used in each station of the Central Weather Bureau (CWB) were inherent to erros before April 2003. This thesis uses the meteorological data between 2004 and 2013 from 30 meteorological stations of CWB, in order to update and repair the Taiwan solar repository. This thesis uses third-order equations to fill the database which were lacked in the report of CWB. Next, I set a database in a so-called typical meteorological year (TMY), which represents long term solar data for Taiwan. In assessing the application of solar energy, the meteorological database of typical meteorological year will be used as a reference.
Global-radiation is usually divided into two parts: beam radiation and diffuse-radiation. The diffuse-fraction is a proportion of diffuse component in global-radiation. The extent of diffuse-fraction can affect the way we design solar energy application systems. This research utilizes the diffuse-fraction data measured at Kuei-Jen in Tainan and develops a diffuse-fraction model.
Key words: typical meteorological year (TMY), solar thermal energy, diffuse
INTRODUCTION
Green energy includes: solar energy, wind power, hydroelectric power, tidal energy, biomass energy, geothermal energy, and marine energy. Taiwan is located in a subtropical region. Thus, Taiwan has sufficient sunlight for solar energy applications throughout the year. Solar energy applications are usually divided into two parts: solar thermal applications and solar photovoltaics (PV). Solar thermal applications utilize sunlight irradiating on a collector. This results in a temperature rise of the working fluid, and then uses the working fluid to achieve specific goals. Some examples are: solar energy water heaters and factory reheating of working fluid. Solar photovoltaics (PV) utilize sunlight irradiating on photovoltaic modules. The photovoltaic materials absorb sunlight and cause electricity generation. Photovoltaic wavelength absorption is limited. Therefore, solar thermal applications are more efficient than solar photovoltaics.

DIFFUSE-FRACTION MODELLING
In order to establish a diffusion-fraction model, several important parameters must be calculated. Important parameter explanations and formulas are as follows:

Clearness Index (k_t):
Clearness index is defined as the ratio of global-radiation and extraterrestrial radiation. Determining how much radiation is absorbed by the atmosphere will also make us aware of weather conditions. The formula is as follows:
k_t=I_global/H_0 (1)
I_global: hourly global-radiation.
H_0: hourly extraterrestrial radiation.
Extraterrestrial Radiation (H_0):
Extraterrestrial radiation is defined as sunlight radiation without loss when having passed through the atmosphere. Also, there are limits on the maximum solar radiation reaching the Earth's surface. The formula is as follows:
H_0=(3600*12*G_sc*[1+0.033*((360*N)/365)])/π
*∫_w1^w2▒(cos∅*cosδ*cosw+sin∅*sinδ)dw (2)
G_sc: solar constant(1367 W⁄m^2 ).
∅: Latitude.
N: N days of the year.
ω: hour angle.
δ: Declination.

Diffuse-Fraction (d):
Diffuse-fraction is defined as the ratio of diffuse-radiation and global-radiation. The formula is as follows:
d=I_diffuse/I_global (3)
I_diffuse: diffuse-radiation.
I_global: global-radiation.
This research utilizes the diffuse-radiation data and the global-radiation data measured at Kuei-Jen in Tainan. The regression equation is used to establish a third-order empirical model for diffusion-fraction in Tainan, Taiwan.



TYPICAL METEOROLOGICAL YEAR
A typical meteorological year (TMY) represents the long-term observation years of climate in an area, composed by 12 different typical meteorological months, respectively. TMY’s information can be used for the performance assessment of solar system.
This thesis uses a third-order polynomial equation to correlate the database. The daily meteorological data is composed by average the hourly meteorological data. The formula is as follows:
Daily meteorological data=(∑_(i=1)^24▒x_i )/24 (4)
The long-term cumulative distribution function (CDF) and store-term cumulative distribution function are calculated as follows:
CDF(x_i){█(0 ,x〈x_1@((i-0.5))/n,x_i≤x〈x_(i+1)@1 ,x≥x_n )┤ (5)
Using Finkelstein-Schafer statistics’s (FS statistics) results to compare with the long-term CDF and store-term CDF. The Finkelstein-Schafer statistics (FS statistics) can be used to see which year is closest to the average meteorological datebase. The formula is as follows:
FS statistics=1/N ∑_(i=1)^N▒|〖CDF〗_LT (x_i)-〖CDF〗_ST (x_i)| (6)
Different purposes are used to select a different weighting factor (WF). Weighted statistics is calculated by FS statistics multiplied weighting factor for this year. The formula is as follows:
WS=∑_(i=1)^N▒〖〖(FS statistics)〗_i*〖(WF)〗_i 〗 (7)
Comparing with weighted statistics in different years and picking up the smallest weighted statistics comes out with a typical meteorological month. Typical meteorological year is composed by 12 different typical meteorological months.

CONCLUSION
In this thesis, I utilized the latest and most accurate database of diffuse-radiation in Kuei-Jen.We calculated the absolute error and the relative error of Shadow Band Stand (Model SBS) and AutoMatic Solar Tracker (Model SMT). The absolute error of data obtained between SBS and SMT become larger when the sun is closer to noon. The relative error of data is larger when the sun is closer to sunrise or sunset. The regression equation was used to establish a third-order empirical model for diffusion-fraction. Developed diffusion-fraction model in Taiwan is shown in the section 4.1.1.
This thesis uses the meteorological data from Taiwan’s 30 meteorological stations of CWB, from 2004 to 2013, in order to update and repair the Taiwan solar repository. The typical meteorological years for the 30 CWB’s stations in Taiwan are respectively determined which is presented in the section 4.2.2.

目錄
摘要 I
致謝 VII
目錄 VIII
表目錄 X
圖目錄 XII
符號說明 XV
第１章 緒論 1
1.1 前言 1
1.2 文獻回顧 3
1.2.1 不同來源之全日空輻射量資料比較 3
1.2.2 全日空輻射計之效驗與分析 4
1.2.3 漫射率模組與實驗值比較分析 6
1.2.4 經典氣象年(TMY2) 9
1.3 研究動機 10
第２章 實驗設備介紹與架設方法 11
2.1 實驗設備介紹 11
2.1.1 全日空輻射計 11
2.1.2 漫射率量測裝置 11
2.1.3 訊號收集裝置 12
2.2 實驗設備架設方法及規範 12
2.2.1 全日空輻射計之架設方法及規範 12
2.2.2 漫射率量測裝置之架設方法及規範 13
第３章 實驗方法及理論分析 14
3.1 漫射率模組之參數介紹及理論分析 14
3.1.1 晴空指數(clearness index) 14
3.1.2 漫射率(diffuse fraction) 15
3.1.3 國立成功大學歸仁校區之數據分析方法 16
3.1.4 實際與模擬數據之比較及分析方法 17
3.2 經典氣象年(TMY2) 18
3.2.1 經典氣象年之簡介 18
3.2.2 經典氣象年之選取方法 19
3.2.3 缺少數據之補齊方法 23
3.2.4 加權函數之挑選 25
3.2.5 選取經典氣象年之範例及原理 27
第４章 結果與討論 33
4.1 漫射率之實際與模擬數據比較 33
4.1.1 實際數據之處理流程 33
4.1.2 模擬模型之選取 34
4.1.3 實際與模擬數據之比較及討論 36
4.2 經典氣象年之結果與討論 37
4.2.1 缺少氣象資料之數量 37
4.2.2 不同加權函數下之經典氣象年 38
4.2.3 選取經典氣象年之討論 39
第５章 結論與建議 40
5.1 結論 40
5.2 建議與未來工作 41
參考文獻 42

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