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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 江昭皚(Joe-Air Jiang) | |
dc.contributor.author | Huan-Chieh Chiu | en |
dc.contributor.author | 邱奐絜 | zh_TW |
dc.date.accessioned | 2021-06-17T06:32:46Z | - |
dc.date.available | 2021-08-21 | |
dc.date.copyright | 2018-08-21 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-08-16 | |
dc.identifier.citation | 許志義。2000。由 729,921 大停電談電力永續發展政策。經濟前瞻67: 114-117.
「輸電工程作業手冊」。2014 年1 月。台北:台灣電力公司。 葉明志。2008。輸電線路雷擊、絕緣及容量提升之設計技術。台灣電力公司輸工處北施處。 羅俊雄、黃奇瑜、溫國樑、林美聆、蕭江碧、張國鎮、施邦築、許銘熙、林其璋、王鴻楷、簡文郁、柴駿甫、鄧崇任、葉錦勳、黃炯憲、劉季宇、鄧慰先、張順益、葉勇凱、賴美如、王聖明、鐘立來、廖文義、李政寬、許健智。1999。九二一集集大地震全面勘災精簡報告。台北:國家地震工程研究中心。 顧欣怡、王信凱、鄭安孺、高慧萱、陳怡彣、呂國臣。2011。高解析度網格點氣象分析系統。交通部中央氣象局 100 年天氣分析與預報研討會論文彙編。 Abraham, A. P., and S. Ashok. 2012. Gyro-accelerometric SAG analysis and online-monitoring of transmission lines using Line Recon Robot. In “IEEE India Conference (INDICON), 2012 Annual IEEE”, 1036-1040, Kochi, India: IEEE. Adomah, K., Y. Mizuno, and K. Naito. 2000. Probabilistic assessment of the sag in an overhead transmission line. IEEJ Transactions on Power and Energy. 120(10): 1298-1303. Anderson, P. L., and I.K. Geckil. 2003. Northeast blackout likely to reduce US earnings by $6.4 billion. Anderson Economic Group. Chen, G., X. Wang, J. Wang, J. Liu, T. Zhang, and W. Tang. 2012. Damage investigation of the aged aluminium cable steel reinforced (ACSR) conductors in a high-voltage transmission line. Engineering Failure Analysis. 19: 13-21. De Maria, L., E. Golinelli, and U. Perini. 2017. Innovative optical systems and sensors for on line monitoring of high voltage overhead lines and power components. In “IEEE AEIT International Annual Conference, 2017”, 1-6, Seoul, Korea: IEEE. de Villiers, W., J. H. Cloete, L. M. Wedepohl, and A. Burger. 2008. Real-time sag monitoring system for high-voltage overhead transmission lines based on power-line carrier signal behavior. IEEE Transactions on power delivery. 23(1): 389-395. Dong, X. 2016. Analytic Method to Calculate and Characterize the Sag and Tension of Overhead Lines. IEEE Transactions on Power Delivery. 31(5): 2064-2071. Douglass, D., W. Chisholm, G. Davidson, I. Grant, K. Lindsey, M. Lancaster, ... and J. Reding. 2016. Real-time overhead transmission-line monitoring for dynamic rating. IEEE Transactions on Power Delivery. 31(3): 921-927. Douglass, D. A. 1988. Weather-dependent versus static thermal line ratings (power overhead lines). IEEE Transactions on Power Delivery. 3(2): 742-753. Du, Y., and Y. Liao. 2012. On-line estimation of transmission line parameters, temperature and sag using PMU measurements. Electric Power Systems Research. 93: 39-45. Hayt, W. H., and J. A. Buck. 1981. Engineering electromagnetics (Vol. 6). New York: McGraw-Hill. IEEE Std. 738-2012 (Revision of IEEE Std. 738-2006). 2012. IEEE standard for calculating the current-temperature of bare overhead conductors. Jiang, J. A., Y. T. Liang, C. P. Chen, X. Y. Zheng, C. L. Chuang, and C. H. Wang. 2016. On dispatching line ampacities of power grids using weather-based conductor temperature forecasts. IEEE Transactions on Smart Grid. Justus, C. G., and A. Mikhail. 1976. Height variation of wind speed and wind distributions statistics. Geophysical Research Letter. 3(5): 261-264. Khawaja, A. H., Q. Huang, J. Li, J., and Z. Zhang. 2017. Estimation of current and sag in overhead power transmission lines with optimized magnetic field sensor array placement. IEEE Transactions on Magnetics. 53(5): 1-10. Kim, S. D., and M. M. Morcos. 2013. An application of dynamic thermal line rating control system to up-rate the ampacity of overhead transmission lines. IEEE Transactions on power delivery. 28(2): 1231-1232. Lijia, R., L. Hong, and L. Yan. 2012. On-line monitoring and prediction for transmission line sag. In “IEEE Condition Monitoring and Diagnosis (CMD), 2012 International Conference”, 813-817, Bali, Indonesia: IEEE. McElvain, F. R., and S. S. Mulnix. 2000. Statistically determined static thermal ratings of overhead high voltage transmission lines in the Rocky Mountain region. IEEE Transactions on Power Systems. 15(2): 899-902. Minkel, J. R. 2008. The 2003 Northeast Blackout--Five Years Later. Scientific American, 13. National Energy Technology Laboratory, U.S. Dept. of Energy. 2007. A system view of the modern grid, Appx. B2: sensing and measurement. Oleinikova, I., A. Mutule, and M. Putnins. 2014. PMU measurements application for transmission line temperature and sag estimation algorithm development. In “IEEE Power and Electrical Engineering of Riga Technical University (RTUCON), 2014 55th International Scientific Conference”, 181-185, Riga, Latvia: IEEE. Ramachandran, P., and V. Vittal. 2006. On-line monitoring of sag in overhead transmission lines with leveled spans. In “IEEE Power Symposium, 2006. NAPS 2006. 38th North American”, 405-409, Carbondale, USA: IEEE. Ren, L., J. Xiuchen, and S. Gehao. 2008. Research for dynamic increasing transmission capacity. In “Condition Monitoring and Diagnosis, 2008. CMD 2008. International Conference”, 720-722, Beijing, China: IEEE. Romero, J. J. 2012. Blackouts illuminate India's power problems. IEEE spectrum. 49(10). Saadat, H. 1999. Power system analysis. McGraw-Hill. Schaefer, R. A. 1950. Calculations of maximum sag of a transmission line with an ice load on one span. Toussaint, K., N. Pouliot, and S. Montambault. 2009. Transmission line maintenance robots capable of crossing obstacles: State‐of‐the‐art review and challenges ahead. Journal of Field Robotics. 26(5): 477-499. Tumelo-Chakonta, C., and K. Kopsidas. 2011. Assessing the value of employing dynamic thermal rating on system-wide performance. In “IEEE Innovative Smart Grid Technologies (ISGT Europe), 2011 2nd IEEE PES International Conference and Exhibition”, 1-8, Manchester, UK: IEEE. Wang, C. H., X. Y. Zheng, Y. C. Yang, C. Y. Tseng, K. S. Tseng, and J. A. Jiang. 2017. A Novel Transmission Line Safety Monitoring System for Smart Grid. In “Smart Grid Inspired Future Technologies”, 35-45, London, UK: Springer, Cham. Wang, H., S. Han, L. J. Lv, and L. J. Jin. 2017. Transmission line sag measurement based on single aerial image. In “IEEE Mechatronics and Machine Vision in Practice (M2VIP), 2017 24th International Conference”, 1-5, Auckland, New Zealand: IEEE. Wang, W., and S. Pinter. 2014. Dynamic line rating systems for transmission lines. US DOE, April. Wong, J. J., C. T. Su, C. S. Liu, and C. L. Chang. 2007. Study on the 729 blackout in the Taiwan power system. International Journal of Electrical Power & Energy Systems. 29(8): 589-599. Yan, Y., W. Bao, J. Xin, H. Lin, Z. Li, and H. Zhong. 2015. A thermal model based dynamic rating system for overhead transmission lines. In “Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2015 5th International Conference”, 2758-2763, Changsha, China: IEEE. Yu, W., & M. G. Pollitt. 2009. Does Liberalisation cause more electricity blackouts? Evidence from a global study of newspaper reports. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72276 | - |
dc.description.abstract | 對於世界現行輸電網而言,「輸電效率」與「電網安全性」乃輸配電公司之兩大考量,而歷經國內外數次大停電(如美加大停電、七二九大停電、八一五大停電、印度大停電…等)所帶來的衝擊與影響,輸電網的重要性已自不待言。欲提升電網安全性、輸配電裕度與彈性,可藉由直接監測輸電線與其附近環境的即時參數與資訊(如電流、線溫、環境溫度…等),進一步分析電網之即時情況,供輸配電單位做安全監測與輸配電評估。而若需大範圍監測電網安全,最佳方案即將「物聯網」導入電網,以無線監測的技術,做為輸電網安全監測系統的基礎。「物聯網」一詞可說是過去十年最火熱的科技名詞之一,利用因地制宜的前端設備與無線感測器網路,蒐集所需參數並進行分析,將分析結果反饋並用於服務使用者。然而,高壓輸電線周圍之超強電磁波會嚴重干擾無線通訊與電子設備運行,故其技術屏障相較其他物聯網產業高得多。本團隊歷經多年研究,成功克服此技術屏障,開發出一套搭配可抗電磁波干擾之超高壓輸電線實時監測之物聯網系統,量測多種輸電線參數,其中,本論文所分析之參數為監測設備所量測之三軸加速度,計算輸電線之垂度,以避免輸電線垂降過度、觸碰到地面或植被進而造成的接地故障。本研究主要分析系統於三個月內穩定運行所蒐集之數據,計量輸電線垂降值,並且與理論值做比對,其相關係數高達0.8603,平均絕對誤差僅0.44%,輔以實地量測結果驗證,足以證明此系統之準確性、可靠性與耐久性。此外,本研究亦列出分別懸掛於三相線路之設備量測資料並加以對照,充分顯示物聯網技術應用於超高壓輸電網內之可行性。此系統不僅能克服現在其他電網監測方法所無法克服之可行性與建置成本問題,其無線通訊與物聯網技術更使系統具有可廣佈、進行大範圍電網監測的絕佳優點。本研究之目的與願景為針對輸電網之情況進行實時分析,進而提供電力公司適當的調度建議,不僅提升調度彈性,更能確保電網運行無虞,為國家安全與產業發展盡一份心力。 | zh_TW |
dc.description.abstract | For power companies around the world, transmission efficiency and power grid safety are two of the most important issues. The importance of the power grid safety goes without saying, after witnessing the impacts of a few power outages, such as the Northeast blackout of 2003, the 729 and 815 blackouts in Taiwan, and the 2012 India blackouts. The safety, efficiency and flexibility of high/extra-high voltage transmission lines can be improved by conducting real-time analyses on the parameters relating to the directly monitored transmission lines and their surrounding areas. The real-time information is criterial to power companies in power grid safety monitoring and power dispatch decision making. To monitor the safety of large scaled power grids, the best solution is to introduce “Internet of Things (IoT)” to power grids and use an IoT-based safety monitoring system on power grids. “IoT” has been one of the hottest terms in technology industries. An IoT monitoring system employs a wireless sensor network at the front-end sensing module to collect required local parameters for further analysis, and the analysis results can be used to improve various services. Nevertheless, the strong electromagnetic field around high/extra-high voltage lines is quite a technical barrier for electronic devices, which is much more challenging compared to other IoT applications. But the technical barrier has been removed and a reliable monitoring system for power grids that directly measures parameters on and around high voltage transmission lines in real time has been developed. In this research, a transmission line sag system is proposed. In this system, a three-axis accelerometer is used to measure transmission line sags, preventing the monitored transmission line from touching objects beneath it, which might lead to ground fault and even large-scale power failures. This study analyzes measured sag values collected during a seven-month stable operation and compares the measured values with theoretical values. The correlation coefficient of the two types of the sag values is 0.8603, and the mean absolute percent error (MAPE) is only 0.44%. Moreover, the accuracy of the measured sag values has been verified by comparing the values with field measurements. These results confirm the high accuracy, reliability and durability of the proposed sag monitoring system. In addition, this study examines the measurement results obtained from the devices placed on the three phases of a transmission line to verify the feasibility of applying the IoT technology to EHV transmission systems. The results show that this proposed sag monitoring system has overcome the challenge of the strong electromagnetic field around a transmission line with high/extra-high voltage. It reduces excessive construction costs when using other power grids monitoring systems. By adopting the IoT technology, the proposed system is able to be widely implemented in large-scale power grid monitoring. And, the line sag information can be used as power dispatch suggestions. The research results and conclusion provide criterial information not only to improve the flexibility of power dispatch but also to ensure the safety of power grids. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T06:32:46Z (GMT). No. of bitstreams: 1 ntu-107-R05631030-1.pdf: 6279735 bytes, checksum: 2953be4c290dcb604623a9177d364556 (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 誌謝 i
中文摘要 v Abstract vi Table of Contents ix List of Figures xiii List of Tables xvii Chapter 1 Introduction 1 1.1 Background 1 1.2 Motivation and Purpose 3 1.3 Thesis Organization 6 1.4 Reach Contributions 6 Chapter 2 Literature Review 9 2.1 Brief Overview of Taipower System 9 2.2 Transmission Conductors in Taiwan 11 2.3 Sag Measurements 14 2.3.1 Mechanical Estimations 15 2.3.2 Signal Information 17 2.3.3 On-line Robot 19 2.3.4 IR Laser Scanning 20 2.3.5 Image Processing 21 2.3.6 Magnetic Measurement 22 2.4 Summary 22 Chapter 3 Materials and Methods 27 3.1 Sag Monitoring System 27 3.1.1 Sag Measuring Devices 30 3.1.2 Experimental Information and Parameters 34 3.2 Line Equations 36 3.2.1 Basic Catenary Equations 36 3.2.2 Catenary Equations at Inclined Spans 38 3.3 Line Temperature Obtained from IEEE Std. 738-2012 42 Chapter 4 Results 47 4.1 Sag Values Obtained from Catenary Equations 47 4.1.1 Catenary Equation with the Influence by Heat Expansion 48 4.1.2 Theoretical Line Temperature Calculation Based on the IEEE Standard 738-2012 52 4.2 Sag Values from Sag Sensors 65 4.2.1 Sag Values Calculated from Angle 66 4.2.2 Comparison of the Measurement Results and Theoretical Results 68 4.2.3 Measuring Results from Different Sag Sensors 80 4.3 Sag Values Obtained from the Field Measurements 85 Chapter 5 Conclusions and Future Work 89 References 91 Appendix 95 Parabolic Approximation 95 | |
dc.language.iso | en | |
dc.title | 基於物聯網之架空輸電線路弛度監測系統 | zh_TW |
dc.title | An IoT-based Sag Monitoring System for Overhead Transmission Lines | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 吳立成(Li-Cheng Wu),李建興(Chien-Hsing Lee),蕭瑛東(Ying-Tung Hsiao),曾傳蘆(Chwan-Lu Tseng) | |
dc.subject.keyword | 智慧電網,輸電線垂降監測,物聯網,超高壓輸電網, | zh_TW |
dc.subject.keyword | Smart grids,sag monitoring system,Internet of Things (IoT),EHV transmission systems, | en |
dc.relation.page | 97 | |
dc.identifier.doi | 10.6342/NTU201803772 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2018-08-16 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物產業機電工程學研究所 | zh_TW |
顯示於系所單位: | 生物機電工程學系 |
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