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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 江昭皚(Joe-Air Jiang) | |
| dc.contributor.author | Jie-Jyun Wan | en |
| dc.contributor.author | 萬倢君 | zh_TW |
| dc.date.accessioned | 2021-06-16T05:08:30Z | - |
| dc.date.available | 2019-08-20 | |
| dc.date.copyright | 2014-08-25 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-08-19 | |
| dc.identifier.citation | Abbott, S., S. Abdelkader, L. Bryans, and D. Flynn. 2010. Experimental validation and comparison of IEEE and CIGRE dynamic line models. In 'Proc. 45th International Universities Power Engineering Conference (UPEC)', 1-5. Cardiff, Wales: UPEC.
Alamaniotis, M., A. Ikonomopoulos, and L. H. Tsoukalas. 2012. Evolutionary Multiobjective Optimization of Kernel-Based Very-Short-Term Load Forecasting. IEEE Trans. Power Syst. 27(3): 1477–1484. Beran, P., and W. Silva. 2001. Reduced-Order Modeling: New Approaches for Computational Physics. AIAA Paper No. 2001-0853. Reno, NV: AIAA. Black, J., S. Connor, and J. Colandairaj. 2010. Planning network reinforcements with dynamic line ratings for overhead transmission lines. In 'Proc. 45th International Universities Power Engineering Conference (UPEC)', 1-6. Cardiff, Wales: UPEC. Berkooz, G. 1992. Observations on the proper orthogonal decomposition. In 'Studies in Turbulence', ed. 229-247. New York: Springer. Callahan, P. M., and D. A. Douglass. 1988. An experimental evaluationof a thermal line uprating by conductor temperature and weather monitoring. IEEE Trans. Power Del. 3(4): 1960-1967. Cheema, J., A. Clark, J. Kilimnik, C. Pavlovski, D. Redman, and M. Vu. 2011. Towards Smart Grid Dynamic Ratings. AIP Conf. Proc. 1373(1): 3-17. Chu, R. F. 1992. On selecting transmission lines for dynamic thermal line rating system implementation. IEEE Trans. Power Syst. 7(2):612-619. Cigre Working Group 22.12. 1997. The thermal behavior of overhead conductors. CIGRE, ELECTRA. 174(10): 59-69. Cigre Working Group B2.12. 2006. Guide for selection of weather parameters for bare overhead conductor ratings. Cigre Brochure. 299(8): 9-17. Deb, K., A. Pratap, S. Agarwal, and T. Mejarivan. 2002. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2): 182-197. Douglass, D. A., and A. A. Edris. 1996. Real-time monitoring and dynamicthermal rating of power transmission circuits. IEEE Trans. Power Del. 11(3): 1407-1417. Douglass, D. A., D. C. Lawry, A. A. Edris, and E. C. Bascom. 2000. Dynamic thermal ratings realizecircuit load limits. IEEE Comput. Appl. Power. 13(1): 38-44. Dowell, E. H., K. C. Hall, J. P. Thomas, R. Florea, B. I. Epureanu, and J. Heeg. 1999. Reduced Order Models in Unsteady Aerodynamics. Engineering Mechanics. 6(4): 229-252. Everson, R., and L. Sirovich. 1995. The Karhunen-Loeve for Gappy Data. J. Opt. Soc. Am. A. 12(10): 1657-1664. Foss, S. D., S. H. Lin, R. A. Maraio, and H. Schrayshuen, 1988. Effect of variability in weather conditions on conductor temperature and the dynamic rating of transmission lines. IEEE Trans. Power Del. 3(4): 1832-1841. Holmes, P., J. L. Lumley, and G. Berkooz. 1996. Turbulence Coherent structures, Dynamical Systems and Symmetry. 2nd ed. USA: Cambridge University Press. Hosek, J., P. Musilek, E. Lozowski, and P. Pytlak. 2011. Effect of time resolution of meteorological inputs on dynamic thermal rating calculations, IET Gen. Transm. Distrib. 5(9): 941-947. Howington, B. S., and G. J. Ramon. 1987. Dynamic thermal line rating summary and status of the state-of-the-art technology. IEEE Trans. Power Del. 2(3): 851-858. Hur, K., M. Boddeti, N. D. R. Sarma, J. Dumas, J. Adams, and S. Chai. 2010. High wire act: ERCOT balances transmission flows for Texas-size savings using its dynamic thermal ratings application. IEEE Power Energy. 8(1):37-45. IEC/TR 61597-1995. 1995. Overhead electrical conductors – Calculation methods for stranded bare conductors. IEEE. 2010. WG12 Report Highlights. USA: IEEE-TPC Available at: http://www.ieee-tpc.org/IEEE-TPC_RatingWith738_26July2010.pdf. Accessed 10 October 2013. IEEE std 738-2006 (Revision of IEEE Std 738-1993). 2007. Standard For Calculating The Current-Temperature of Bare Overhead Conductors. Jolliffe, I. T., 1986. Principal Component Analysis. 2nd ed. New York: Springer. Karhunen, K., 1946. Uber Lineare Methoden in der Wahrscheinlichkeitsrechnung. Ann. Acad. Sci. Fennicae. Ser. A. I. Math.-Phys. 37: 1-79. Kazerooni, A. K., J. Mutale, M. Perry, S. Venkatesan, and D. Morrice. 2011. Dynamic thermal rating application to facilitate wind energy integration. In 'Proc. PowerTech, 2011 IEEE Trondheim', 1-7. Trondheim, Noruega: PowerTech IEEE. Kim, D. M., J. M. Cho, H. S. Lee, H. S. Jung, and J. K. Kim. 2006. Prediction of Dynamic Line Rating Based on Assessment Risk by Time Series Weather Model. In 'Proc. International Conference on PMAPS', 1-7. Stockholm: PMAPS. Kirby, M., and L. Sirovich. 1990. Application of the Karhunen-Loeve Procedure for the Characterization of Human faces. IEEE TPAMI. 12(1): 103 - 108. Kosambi, D. 1943. Statistics in function space. Journal of Indian Mathematical Society. 7: 76-88. LeGresley, P. A., and J. J. Alonso. 2001. Investigation of Non-Linear Projection for POD Based Reduced Order Models for Aerodynamics. AIAA Paper No. 2001-0926. Reno, NV: AIAA. Liang, Y.C., H. P. Lee, S. P. Lim, W. Z. Lin, K. H. Lee, and C. G. Wu. 2002. Proper Orthogonal Decomposition and its Applications-Part I: Theory. JSV. 252(3): 527-544. Loeve, M. 1948. Fonctions Al’eatoires du Second Ordre. Processus stochastiques et mouvement Brownien, P. Levy ed., Paris, France: Gauthier-Villars. Marler, R. T., and J. S. Arora. 2004. Survey of multi-objective optimization methods for engineering. Struct. Multidisc. Optim. 26(6): 369–395. Newman, A. J. 1999. Modeling and Reduction with Application to Semiconductor Processing. PhD dissertation. College Park: University of Maryland. Obukhov, M. A. 1954. Statistical description of continuous fields. Transactions of the Geophysical International Academy Nauk USSR. 24: 3-42. Pareto, V. 1906. Manuale di Economia Politica. 1st ed. Milano, Italy: Societa Editrice Libraria. Pougachev, V. S. 1953. General theory of the correlations of random functions. Izvestiya Akademii Nauk USSR. 17: 1401-1402. Pytlak, P., and P. Musilek. 2010. An intelligent weather-based system to support optimal routing of power transmission lines. In 'Proc. IEEE Electric Power and Energy Conference (EPEC)', 1-6. Halifax, NS: EPEC. Ren, L., X. Jiang, G. Sheng, and W. Bo. 2008. Design and calculation method for dynamic increasing transmission line capacity. WSEAS Trans. Circuits Syst. 7(5): 348 -357. Romanowski, M. C. 1996. Reduced Order Unsteady Aerodynamic and Aeroelastic Models using Karhunen-Loeve Eigenmodes. AIAA Paper No. 96-194. New Orleans, LA.: AIAA. Rona, A., E. J. Brooksbank. 2003. POD analysis of cavity flow instability. AIAA Paper No. 2003-0178. Reno, NV: AIAA. Saied, M. M. 2007. Assessing the dynamic rating of overhead transmission lines. Eur. Trans. Elect. Power. 17(5): 526-536. Schmidt, N. P. 1999. Comparison between IEEE and CIGRE ampacity standards. IEEE Trans. Power Del. 14(4): 1555-1562. Shaker, H., M. Fotuhi-Firuzabad, and F. Aminifar. 2012. Fuzzy Dynamic Thermal Rating of Transmission Lines. IEEE Trans. Power Del. 27(4):1885-1892. Sirovich, L. 1987. Turbulence and the Dynamics of Coherent Structures, Part 1: Coherent Structures. Quarterly of Applied Mathematics. 45(3): 561-571. Staszewski, L., and W. Rebizant. 2010, The Differences between IEEE and CIGRE Heat Balance Concepts for Line Ampacity Considerations. In 'Proc. Modern Electric Power Systems (MEPS), 2010 Proceedings of the International Symposium', 1-4. Wroclaw, POLAND: MEPS. Wan, H., J. McCalley, and V. Vittal. 1999. Increasing thermal rating by risk analysis. IEEE Trans. Power Syst. 14(3):815-828. Yu, F. R., P. Zhang, W. Xiao, and P. Choudhury. 2011. Communication systems for grid integration of renewable energy resources. IEEE Network. 25(5): 22-29. Zhang, P., M. Shao, A. R. Leoni, D. H. Ramsay, and M. Graham. 2008. Determination of static thermal conductor rating using statistical analysis method. In 'Proc. Third Int. Conf. Electric Utility Deregulation and Restructuring and Power Technologies (DRPT)', 1237-1243. Nanjuing, China: DRPT. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/55789 | - |
| dc.description.abstract | 動態熱額定容量(Dynamic thermal rating, DTR)技術用來管理電力系統輸電線路是有效和適當的方法。動態熱容量的評估採用輸電線上的溫度感測器來監測架空輸電線路的工作溫度,藉以計算出每個輸電線路的電流裕度,達到輸電安全的狀況下有效提升電網的輸電效益。然而,部署大量的溫度感測器可能不是一個可行的選擇,因為設備成本過高,且增加了電網整體結構的複雜性。本研究以臺灣中部地區的345 kV超高壓輸電線為例,目標是部署最少數量的溫度感測器,利用有放置溫度感測器的感測值可以有效的精準估計所有輸電線線路的導體溫度。本文提出的配置方法,利用特徵正交分解(Proper orthogonal decomposition, POD)進行溫度的特徵擷取,再利用瀰集進化演算法(Memetic algorithm, MA)決定最小數量的溫度感測器和其最佳感測器位置來追踪傳輸線的導體溫度和準確地估計完整的導體溫度。結果顯示此提出的方法可以只需要五分之一的感測器即可估測整體的輸電線線路溫度,並且有高精準度的導體溫度估測,其均方根誤差小於1。這種方法可以提供操作電網系統的熱容量增加和過載風險評估的可靠技術。 | zh_TW |
| dc.description.abstract | Dynamic thermal rating (DTR) technique is an effective and proper method to manage transmission lines in power system. Dynamic thermal rating utilizes on-line thermal sensors to monitor the operating temperature of overhead transmission lines, and calculates the ampacity margin of the transmission lines. The power transmission efficiency could be improved while under the safe condition. However, deploying a large number of thermal sensors may not be a viable option, because of high equipment costs and increasing the structural complexity of the power grid. A case study of the 345 kV extra high voltage transmission lines in central Taiwan was presented. The goal in this study is to allocate the minimum number of thermal sensors. Using the measurements where deploy the thermal sensor, the conductor temperature of whole transmission lines can be efficiently accurate estimation. This paper proposed an allocating placement method which is using the proper orthogonal decomposition (POD) for temperature feature extraction, and then using the memetic algorithm (MA) for determining the minimum number of thermal sensors and the optimal sensor placement to track the temperature of transmission lines and accurately estimate the full conductor temperatures. The results show that this method can be made only needs the one-fifth of sensors to estimate the conductor temperature of entire transmission line spans with high accuracy. The average mean square error is less than 1. This method can provide the operating power system a dependable technique for thermal capacity increment and the evaluation of overload risk. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T05:08:30Z (GMT). No. of bitstreams: 1 ntu-103-R01631036-1.pdf: 4376964 bytes, checksum: dbc7415927107fd45b81dfbf2e6ff032 (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
Acknowledgements ii 中文摘要 iii Abstract iv List of Figures viii List of Tables ix Chapter 1 Introduction 1 1.1 Background 1 1.2 Motivations 2 1.3 Organization of the Master Thesis 4 Chapter 2 Literature Review 6 2.1 Dynamic Thermal Rating 6 2.2 Standards for Dynamic Thermal Rating 9 2.3 Proper Orthogonal Decomposition 10 Chapter 3 Sensor Placement Problem 15 3.1 Overview 15 3.2 Conductor Temperature Calculation Method 18 3.3 The Sensor Placement Problem (SPP) 21 3.3.1 Proper Orthogonal Decomposition 25 3.3.2 Memetic Algorithm (MA) 28 3.3.3 Fitness Function 29 Chapter 4 Simulation and Results 35 4.1 Feature Election 36 4.2 Performance 39 4.2.1 Comparison 40 4.2.1.1 Region 41 4.2.1.2 Lines 47 Chapter 5 Conclusion and Future Work 49 5.1 Conclusion 49 5.2 Future Work 50 Reference 51 | |
| dc.language.iso | en | |
| dc.subject | 動態熱額定容量 | zh_TW |
| dc.subject | 導體溫度估計 | zh_TW |
| dc.subject | 輸電線 | zh_TW |
| dc.subject | 最佳感測器位置 | zh_TW |
| dc.subject | conductor temperature estimation | en |
| dc.subject | dynamic thermal rating | en |
| dc.subject | transmission line | en |
| dc.subject | optimal sensor placement | en |
| dc.title | 最佳化感測器部署應用於超高壓輸電線導體溫度估算 | zh_TW |
| dc.title | Optimal Sensor Placement for Conductor Temperature Estimation of Overhead Extra-High Voltage Power Transmission Lines | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 俞齊山(Chi-Shan Yu),王永鐘(Yung-Chung Wang),艾群(Chyung Ay) | |
| dc.subject.keyword | 動態熱額定容量,導體溫度估計,輸電線,最佳感測器位置, | zh_TW |
| dc.subject.keyword | dynamic thermal rating,conductor temperature estimation,transmission line,optimal sensor placement, | en |
| dc.relation.page | 55 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2014-08-19 | |
| 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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