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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 韓仁毓(Jen-Yu Han) | |
| dc.contributor.author | Ying-Chu Chen | en |
| dc.contributor.author | 陳映竹 | zh_TW |
| dc.date.accessioned | 2021-05-20T00:54:39Z | - |
| dc.date.available | 2023-07-08 | |
| dc.date.available | 2021-05-20T00:54:39Z | - |
| dc.date.copyright | 2020-07-17 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-07-15 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/8447 | - |
| dc.description.abstract | 隨著氣候變遷、能源枯竭等議題受到高度重視,各國積極發展綠色能源來提高整體發電量中的再生能源發電比例,也因此使水力發電、風力發電及太陽光電成為各國發展再生能源的投資重點,其中又以太陽光電的成長幅度最大。太陽光電系統對於設置規模更具有彈性,所需設置面積較小,僅利用一般住宅屋頂也可設置,在推廣屋頂型太陽光電的情況下,為了能夠將太陽光電系統的效能最大化,針對都市建物的太陽光電潛力進行詳細的計算與分析會是主要研究重點。 為求出臺灣都市地區更精確且詳細的太陽光電潛力,相較過往臺灣大範圍光電潛力研究中易忽略到建物屋頂細節對光電潛力計算上的影響,本研究使用含有詳細屋頂結構的LOD2三維都市模型,計算出可裝設太陽光電系統之屋頂位置,在屋頂可接收日射量計算上亦將屋頂傾斜角度與朝向納入考量,結合具長期氣候代表性的標準氣象年逐時太陽輻射量資料,使其在太陽光電影響因子的計算上能更全面,最終做出更加貼近現實建物情況且符合未來氣候趨勢的都市太陽光電潛力分析。本研究對臺北市的LOD2建物模型實驗區進行探討,針對實驗區域因陰影遮蔽現象所造成的接收日射量損失做出比較,計算出該接收日射量損失比率大致落在3%上下。在系統發電量推估部分,可得出太陽光電系統發電量的結果主要受太陽輻射量影響,各實驗區的發電量逐月變化趨勢趨近相同,但其變化幅度會依各地的裝置因子與空間因子條件而有所不同產生;此部分亦針對不同模型細緻度對發電量結果造成之差異作探討,將LOD2建物模型與過往研究常使用的LOD1建物模型進行比較,從實驗區的全年系統發電量結果來看,LOD2建物模型所計算出之發電量增加3%上下的推估發電量,證明採用相對於較高細緻度之空間資訊模型對於太陽能發電量推估之可靠度將產生顯著之提升效益。 | zh_TW |
| dc.description.abstract | As issues of climate change and energy depletion have become more important, most countries are actively developing green energy to increase the proportion of renewable energy in the overall power generation. The foci of investment in renewable energy were hydroelectricity, wind power and solar power, and the latter had the largest growth rate. Solar photovoltaic (PV) systems are more flexible in terms of installation scale and require a smaller installation area, and can be installed on the roof of an ordinary residential building. In the context of the promotion of rooftop PV, detailed calculation and analysis of the PV potential of urban buildings is a major research theme to maximize the performance of PV systems. Previous local studies in Taiwan have often neglected the influence of building roof details on the calculation of PV potential. In this study, the LOD2 3D urban model with detailed roof structure is used to calculate the rooftop locations where solar PV systems can be installed. The angle of roof tilt and orientation are also taken into account in the calculation of the amount of solar radiation a roof can receive. Hourly solar radiation data from a typical meteorological year representative of the long-term climate are also incorporated for a more comprehensive assessment of the impact factors of solar PV. The urban PV potential analyzed in this study will be more in line with real-world building conditions and future climate trends. In this study, we calculate the daily loss of received solar radiation due to the shading phenomenon in the LOD2 building model of the experimental areas in Taipei City. The loss is about 3%. As for the projected power generation, the results show that solar radiation is the main influential factor. The trend of power generation by month is similar among all experimental areas, and the monthly variation depends on the installation factors and spatial factors. This study also compares the results with those using the LOD1 building model. A higher amount (about 3%) of power generation can be calculated with the LOD2 building model, indicating that the reliability of the solar PV estimation can be significantly improved by using a more refined spatial information model. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-20T00:54:39Z (GMT). No. of bitstreams: 1 U0001-1507202014245900.pdf: 5789982 bytes, checksum: f9cecf67daa2a928c06450466ac2d036 (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | 口試委員會審定書 i 致謝 ii 中文摘要 iii ABSTRACT iv 目錄 v 圖目錄 vii 表目錄 x 第一章 緒論 1 1.1 研究背景 1 1.2 研究動機與目的 3 1.3 研究流程 4 1.4 論文架構 5 第二章 文獻回顧 6 2.1 太陽光電之影響因子 6 2.2 環境陰影遮蔽分析 11 2.2.1 三維都市模型 11 2.2.2 陰影分析算法 14 2.3 太陽輻射氣象資料 16 2.4 太陽光電潛力 17 2.4.1 以抽樣統計估算之太陽光電潛力 17 2.4.2 以LiDAR資料估算之太陽光電潛力 18 2.4.3 以相關數值圖資估算之太陽光電潛力 19 2.5 小結 20 第三章 研究方法 21 3.1 三維都市建物模型資料處理 21 3.1.1 建物模型結構萃取 22 3.1.2 屋頂結構模型建構 24 3.1.3 建物邊緣線篩除 25 3.2 裝置因子計算 26 3.2.1 太陽光電模組效能 26 3.2.2 太陽能板傾斜角度與朝向 26 3.3 空間因子計算 28 3.3.1 太陽位置與角度 28 3.3.2 逐時陰影遮蔽 30 3.3.3 接收日射量 32 3.4 整合裝置因子與空間因子之系統發電量推估 34 第四章 實驗結果與分析 36 4.1 研究區域與資料介紹 36 4.1.1 LOD1建物模型資料 36 4.1.2 LOD2建物模型資料 37 4.2 實際資料實驗成果 38 4.2.1 屋頂結構模型成果 38 4.2.2 陰影遮蔽成果 40 4.2.3 接收日射量成果 43 4.2.4 系統發電量成果 45 4.3 成果分析與討論 47 4.3.1 太陽能板傾斜角度與朝向分析 47 4.3.2 陰影遮蔽分析 54 4.3.3 接收日射量及系統發電量分析 56 4.3.4 長期氣候變遷所造成之影響推估 59 第五章 結論與建議 61 5.1 結論 61 5.2 未來工作與建議 62 參考文獻 63 | |
| dc.language.iso | zh-TW | |
| dc.title | 利用高細緻三維都市模型於太陽光電潛力分析 | zh_TW |
| dc.title | Utilizing Highly Detailed 3D City Model for the Analysis of Solar Photovoltaic Potential | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 詹瀅潔(Ying-Chieh Chan),甯方璽(Fang-Shii Ning),郭重言(Chung-Yen Kuo) | |
| dc.subject.keyword | 太陽光電,都市屋頂太陽光電潛力,陰影遮蔽分析,標準氣象年, | zh_TW |
| dc.subject.keyword | Photovoltaics,shading analysis,typical meteorological year,urban rooftop photovoltaic potential, | en |
| dc.relation.page | 65 | |
| dc.identifier.doi | 10.6342/NTU202001541 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2020-07-15 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
| dc.date.embargo-lift | 2023-07-08 | - |
| 顯示於系所單位: | 土木工程學系 | |
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