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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 余化龍 | |
dc.contributor.author | Chung-Yi Chen | en |
dc.contributor.author | 陳仲誼 | zh_TW |
dc.date.accessioned | 2021-06-08T00:49:00Z | - |
dc.date.copyright | 2015-07-20 | |
dc.date.issued | 2015 | |
dc.date.submitted | 2015-07-14 | |
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The starting and low wind behavior of a small horizontal axis wind turbine. Journal of Wind Engineering and Industrial Aerodynamics. 92: 1265-1279. 42. Zimmermann, H. J. (2000). An application-oriented view of modeling uncertainty. European Journal of Operational Research. 122(2): 190-198. 43. 4C offshore, 10 Years of Wind Speed Rankings. http://www.4coffshore.com/windfarms/windspeeds.aspx | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/18030 | - |
dc.description.abstract | 近年來綠色能源的開發越來越受重視,而風能的開發技術越趨成熟,且開發成本亦越趨降低,若能有效地評估該區域的風能潛勢並善加利用,則可增加風機廠商投資意願,且可減少化石燃料對環境所造成之負擔。然而在評估一風場之發電量過程中,存在了許多不確定性,從風速分佈、參數之選取、甚至發電量推估都有不確定性存在,若能有效考慮每個環節之不確定性,將更能掌握一地風能分佈概況,使決策者能做出正確的判斷。
本研究採用概似不確定性估計法(Generalized Likelihood Uncertainty Estimation, GLUE)評估風機發電量之不確定性,此方法能將每個模擬值與實測值進行誤差驗證並賦予一適當之權重,以修正模擬結果。本研究亦與前人研究所使用的蒙地卡羅方法進行比較。本研究將澎湖中屯風力電廠2002年至2011年的十年發電資料分為12個月、強風期(1月至3月及10月至12月)、弱風期(4月至9月)以及全年度,共15個模擬情境,進而探討其模擬結果的不確定性。 研究結果發現,概似不確定估計法較蒙地卡羅法能掌握該區域發電概況,在大部分的模擬情境中都有較佳的模擬結果。在弱風的夏季及強風的冬季,發電量變異程度相差不大;而春、秋兩季為風速快慢交接的季節,風速變化較大,不確定性分佈之區間也較大。 | zh_TW |
dc.description.abstract | Recently green energy, including wind energy, is attached great importance. Moreover, with the improvement of wind energy technology the cost of wind energy development is decreasing. If we can properly assess the wind energy potential in a region, we can provide an incentive to investors. In the process of assessing wind power generation, there exists uncertainties, such as distribution of wind speed, selection of parameters, and estimation of wind generating capacity, etc. Considered the uncertainty of each step, the wind energy output can be estimated accurately, then developers can have more information to make right judgments.
This study uses the Generalized Likelihood Uncertainty Estimation (GLUE) to assess the uncertainty of wind energy capacity. By revising the difference between simulation and measured results and giving a proper weight, the GLUE method can give more accurate simulation results than the widely used Monte Carlo method. This study use the data from 2002 to 2011, collected from the wind power plant in Penghu Jhongtun, and divide the data into 15 simulated scenarios, i.e, 12 months, strong wind period (from January to March and October to December), low wind period (April to September) and the whole year, to explore simulation uncertainty. The research results indicate that the GLUE method has better simulation results than Monte Carlo method does. In most of the scenarios, the GLUE method can describe the realities of the situation. This result also shows that the wind power capacity is steady in summer and winter, while in spring and autumn, because the wind speed changes largely, the uncertainty distribution is relatively larger. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T00:49:00Z (GMT). No. of bitstreams: 1 ntu-104-R02622028-1.pdf: 10698634 bytes, checksum: e14b1190f3e2cdbfbb78b498d98c0246 (MD5) Previous issue date: 2015 | en |
dc.description.tableofcontents | 摘要 i
Abstract iii 目錄 v 表目錄 vii 圖目錄 ix 第一章 緒論 1 1.1 前言 1 1.2 文獻回顧 3 1.3 研究動機與目的 9 第二章 理論及研究方法 10 2.1 韋伯機率函數 10 2.2 發電量推估 12 第三章 不確定性分析方法 17 3.1 不確定性研究方法 18 3.2 不確定性因子探討 20 3.3 蒙地卡羅方法 24 3.4 概似不確定性估計法 27 第四章 發電量驗證及方法比較 42 4.1 參數敏感度分析 42 4.2 結果討論與比較 45 第五章 結論及建議 81 5.1 結論 81 5.2 建議 82 參考文獻 83 | |
dc.language.iso | zh-TW | |
dc.title | 應用概似不確定性估計法於風機發電量之推估 | zh_TW |
dc.title | Evaluation of WECS Energy Output by the Generalized
Likelihood Uncertainty Estimation Method | en |
dc.type | Thesis | |
dc.date.schoolyear | 103-2 | |
dc.description.degree | 碩士 | |
dc.contributor.coadvisor | 張倉榮 | |
dc.contributor.oralexamcommittee | 吳毓庭,杜逸龍 | |
dc.subject.keyword | 不確定性分析,風機發電量推估,蒙地卡羅模擬法,概似不確定性估計法, | zh_TW |
dc.subject.keyword | Uncertainty analysis,Wind Power Generation Estimation,Monte Carlo Simulation,Generalized Likelihood Uncertainty Estimation, | en |
dc.relation.page | 87 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2015-07-15 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物環境系統工程學研究所 | zh_TW |
顯示於系所單位: | 生物環境系統工程學系 |
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