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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 蔡進發(Jing-Fa Tsai) | |
dc.contributor.author | Guo-Hao Huang | en |
dc.contributor.author | 黃國豪 | zh_TW |
dc.date.accessioned | 2021-06-17T04:27:44Z | - |
dc.date.available | 2023-08-19 | |
dc.date.copyright | 2018-08-19 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-08-13 | |
dc.identifier.citation | 1. 2010能源產業技術白皮書, 經濟部能源局, Editor. 2010.
2. 呂威賢, 風的故事 從風車道風力發電機, in 科學發展. 2004. p. 6-13. 3. GWEC, Global Wind Report 2016. 2016. 4. Lapira, E., D. Brisset, H. Davari Ardakani, D. Siegel, and J. Lee, Wind turbine performance assessment using multi-regime modeling approach. Renewable Energy, 2012. 45: p. 86-95. 5. Kusiak, A., H. Zheng, and Z. Song, Models for monitoring wind farm power. Renewable Energy, 2009. 34(3): p. 583-590. 6. Uluyol, O., G. Parthasarathy, W. Foslien, and K. Kim. Power curve analytic for wind turbine performance monitoring and prognostics. in Annual conference of the prognostics and health management society. 2011. 7. Jia, X., C. Jin, M. Buzza, W. Wang, and J. Lee, Wind turbine performance degradation assessment based on a novel similarity metric for machine performance curves. Renewable Energy, 2016. 99: p. 1191-1201. 8. 楊其昌, 高斯混合模型在風機預兆式健康管理上的應用研究, in 工程科學及海洋工程學研究所. 2016, 國立臺灣大學: 台北市. p. 95. 9. 詹勳智, 類神經網路在風機預兆式健康管理上的應用研究, in 工程科學及海洋工程學研究所. 2016, 國立臺灣大學: 台北市. p. 71. 10. 葉柏廷, 自組織映射圖在風機預兆式健康管理上的應用研究, in 工程科學及海洋工程學研究所. 2016, 國立臺灣大學: 台北市. p. 67. 11. Hernandez, W., J.L. López-Presa, and J.L. Maldonado-Correa, Power Performance Verification of a Wind Farm Using the Friedman’s Test. Sensors, 2016. 16(6): p. 816. 12. 謝佩鈞, 相似分群方法在風場風機故障檢測的應用研究, in 工程科學及海洋工程學研究所. 2017, 國立臺灣大學: 台北市. p. 124. 13. IEC, IEC TS 61400-26-1: Wind turbines - Part 26-1: Time-based availability for wind turbine generating systems. 2011, International Electrotechnical Comission: Geneva. p. 1-53. 14. IEC, IEC TS 61400-26-2: Wind turbines - Part 26-2: Production-based availability for wind turbines. 2014, International Electrotechnical Comission: Geneva. p. 1-47. 15. Niu, B., H. Hwangbo, L. Zeng, and Y. Ding, Evaluation of alternative power production efficiency metrics for offshore wind turbines and farms. Renewable Energy, 2018. 128: p. 81-90. 16. Staffell, I. and R. Green, How does wind farm performance decline with age? Renewable Energy, 2014. 66: p. 775-786. 17. Shin, D. and K. Ko, Comparative analysis of degradation rates for inland and seaside wind turbines in compliance with the International Electrotechnical Commission standard. Energy, 2017. 118: p. 1180-1186. 18. Epperson, J.F., On the Runge example. Amer. Math. Monthly, 1987. 94(4): p. 329-341. 19. Diaf, S., D. Diaf, M. Belhamel, M. Haddadi, and A. Louche, A methodology for optimal sizing of autonomous hybrid PV/wind system. Energy Policy, 2007. 35(11): p. 5708-5718. 20. Hocaoğlu, F.O., Ö.N. Gerek, and M. Kurban, A novel hybrid (wind–photovoltaic) system sizing procedure. Solar Energy, 2009. 83(11): p. 2019-2028. 21. IEC, IEC 61400-12-1: Power performance measurements of electricity producing wind turbines. 2017, International Electrotechnical Comission: Geneva. p. 1-96. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/70417 | - |
dc.description.abstract | 本研究利用台電澎湖中屯、彰化彰濱、雲林麥寮3處風場的SCADA(Supervisory Control And Data Acquisition)資料進行分析,利用時間可利用率、發電量可利用率及容量因子分析年度風機及風場變化趨勢,結果顯示在時間可利用率的部分中屯風場相較於其他風場最低,因為長時間停機維修,當中最低為2016年的0.731。而在發電量可利用率的部分,彰工在2013至2015年風場逐年衰減,需要持續注意以即早發現問題並維修;麥寮風場則逐年衰退之外也明顯低於彰工的表現,建議立即檢修。而在容量因子的部分,彰工風場的實際容量因子在四年期間逐年遞減;麥寮則發現第一期完工的風機整體表現高於二期風機之情況。
本研究並提出一性能指標作為每日風機性能表現的度量方法,並提供了一套方便計算與提取正常運行資料的方法,建立性能指標參數。計算結果可發現性能指標對於檢測停機、限載或降級等偏離正常發電之情況較為敏感,可以有效觀測出風機異常日子,並可做為提供準確的即時風機表現評斷指標。 | zh_TW |
dc.description.abstract | The SCADA data of the three wind farms of Taipower, which are located in Penghu Zhongtun, Changhua Changkon and Yunlin Mailiao, were used for the analysis using the time-based availability, production-based availability and capacity factor in this study. For the analysis results using time-based availability, the time-based availability of Penghu Zhongtun is the worst when compared to other two wind farms. The lowest is 0.731 in 2016, because of the long-term maintenance. For the analysis results of production-based availability, the production-based availability of Changhua Changkon wind farm was also declining year by year between 2013 and 2015. It needs to pay attention to the wind farm for early detection and maintenance. The production-based availability of Yunlin Mailiao wind farm was declining year by year, and it is also significantly lower than the performance of Changhua Changkon wind farm. It is recommended to repair it immediately.
This study also proposes a performance factor as a measure of daily wind turbine performance, which is convenient for calculation, and provides a set of method to extract normal operating data to establish parameters of performance factor. The measurement results indicate that the performance factor is sensitive to the detection of derated, degraded or abnormal power generation, etc., which can effectively observe the abnormal days of the wind turbines, and can be used as an accurate indicator of the immediate performance of the wind turbines. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T04:27:44Z (GMT). No. of bitstreams: 1 ntu-107-R05525104-1.pdf: 3593618 bytes, checksum: c7949b08762d1dfa3d0dcefdfdaa3769 (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 口試委員審定書 II
摘要 III Abstract IV 總目錄 V 圖目錄 VII 表目錄 IX 第一章 、 緒論 1 1-1研究背景與動機 1 1-2 文獻回顧 2 1-3 研究內容 3 1-4 論文架構 3 第二章 、使用工具及風機指標 4 2-1 三次樣條內插法(Cubic spline interpolation) 4 2-2 風力發電機的可利用率與容量因子 5 2-2-1 時間可利用率 6 2-2-2 發電量可利用率 8 2-2-3 容量因子 10 2-3 性能指標的計算 12 2-4 DBSCAN 14 第三章 、資料前處理 16 3-1 資料介紹 16 3-1-1 澎湖中屯風力發電站資料 17 3-1-2 彰化彰工及雲林麥寮風力發電站資料 17 3-2 異常資料過濾 17 3-3 資訊類別分類 19 第四章 、風機與風場趨勢分析 20 4-1 各年時間可利用率之性能評估 20 4-1-1 澎湖中屯發電站之討論 20 4-1-2 彰化彰工發電站之討論 21 4-1-3雲林麥寮發電站之討論 21 4-2各年容量因子之性能評估 21 4-2-1 澎湖中屯發電站之討論 22 4-2-2 彰化彰工發電站之討論 22 4-2-3 雲林麥寮發電站之討論 23 4-3 各年發電量可利用率之評估 24 4-3-1 澎湖中屯發電站之討論 24 4-3-2 彰化彰工發電站之討論 24 4-3-3 雲林麥寮發電站之討論 25 第五章 、性能指標建立與各指標之比較 26 5-1 性能指標模型建立 26 5-2 計算每日性能指標 28 5-3 每日性能指標之比較 29 5-3-1 性能指標與發電量可利用率之比較 29 5-3-2 性能指標與時間可利用率之比較 30 第六章 、結論與建議 31 6-1 結論 31 6-2 建議 32 參考文獻 33 附圖 35 附表 66 原始程式碼 70 | |
dc.language.iso | zh-TW | |
dc.title | 風機及風場性能指標之研究 | zh_TW |
dc.title | Study on Performance factor of wind turbines and wind farms | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 黃正利,邵揮洲,林恆山,王勝堯 | |
dc.subject.keyword | 風力發電機,性能指標, | zh_TW |
dc.subject.keyword | Wind Turbine,Performance Factor, | en |
dc.relation.page | 89 | |
dc.identifier.doi | 10.6342/NTU201803235 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2018-08-14 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 工程科學及海洋工程學研究所 | zh_TW |
顯示於系所單位: | 工程科學及海洋工程學系 |
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