由於受經濟及法規之影響，現代社會已經無法讓電力系統承受重大的事故，為了增強系統可靠度，世界各地的電力公司已經使用了許多類型之SPS。在設計SPS時主要的關鍵在於系統是否能達到可靠度的要求，現在工業界只有少許的文獻探討評估SPS的可靠度。在本論文中將比較數種適用於評估SPS可靠度之方法，包含可靠度區塊圖、故障樹、馬可夫模型和蒙地卡羅模擬。為了了解輸入資料不確定性對於系統可靠度之影響，利用蒙地卡羅抽樣將輸入參數之不確定性傳遞至可靠度模型中，如果分析過後系統無法達到可靠度要求，靈敏度分析可以用來評估元件的重要性。系統改善的依據就是利用靈敏度分析的結果來做最有效之改善。最後利用台電既設之SPS來說明整個可靠度分析流程。

Due to limitation of economics and legislation, the power system is not allowed serious accident on modern social. In order to enhance system reliability, many types of special protection systems (SPS) have been implemented by utilities around the world. One of the main concerns in the design of an SPS is whether the designed system can achieve the reliability requirement. Currently, the literature that discusses the SPS reliability issue is scarce. In this thesis, a comparison of several techniques suitable for performing reliability assessment of SPS is presented. Discussed reliability models include using reliability block diagram, fault tree analysis, Markov modeling and Monte Carlo simulations. In order to understand the uncertainty effects of input data on the calculated system reliability, Monte Carlo Sampling method is utilized in this study to take the input parameters uncertainty into account in the system modeling. To deal with the problem of not being able to reach the reliability requirement after uncertainty analysis, a sensitivity analysis is proposed to analyze the importance of the components involved in the system. Sensitivity analysis can be used to identity the most effective component in the enhancement the SPS reliability. A Taipower SPS is used in this thesis to explain the proposed reliability assessment methods.

目錄
中文摘要 I
英文摘要 II
目錄 III
圖表目錄 V

第一章 緒論 1
1.1研究背景與動機 1
1.2國外SPS應用實例 7
1.3 SPS應用於台電系統運轉之經驗 10
1.4 SPS可靠度分相關研究文獻回顧 16
1.5論文架構 28

第二章 特殊保護系統之可靠度分析 29
2.1特殊保護系統設計流程 29
2.1 可靠度定性分析 33
3.1.1 故障模式影響分析 34
2.2 可靠度定量分析 35
2.2.1可靠度分析方法 35
2.2.1.1可靠度區塊圖分析法 35
2.2.1.2故障樹分析方法 39
2.2.1.3 馬可夫模型 47
2.2.1.4 蒙地卡羅模擬 50
2.2.1.5 系統分解法 52
2.2.2 不確定性因素分析 57
2.2.3 靈敏度分析 59
2.3 可靠度定量分析方法之比較 68

第三章 實例分析 71
3.1台電冬山 SPS 71
3.2可靠度定量分析結果 73
3.3不確定性分析結果 78
3.4 靈敏度分析結果 80
3.5 冬山SPS可能的改善方案分析 83
第四章 結論及未來研究方向 86
4.1 結論與建議 86
4.2 未來研究方向 88
參考文獻 89

附錄A-元件PFD之計算 91
附錄B-可靠度計算程式碼 95

參考文獻
[1] System Protection Schemes in Power Networks, CIGRE Task Force 38.02.19 (Convener: D. Karlsson), 2001.
[2] LeReverend, B. K., and Anderson, P. M., “Industry experience with Special Protection Schemes,” IEEE Transactions on Power Systems, Vol. 11, No. 3, Aug. 1996, pp. 1166-1179.
[3] McCalley, J. D., and Fu, W., “Reliability of Special Protection Systems,” IEEE Transactions on Power Systems, Vol. 14, No. 4, Nov. 1999, pp. 1400-1406.
[4] Abi-Samra, N., McCalley, J. D., Zhao, S., Fu, W., Vittal, V., “Risk assessment for special protection systems,” IEEE Transactions on Power Systems, Vol. 17, Issue: 1 , Feb. 2002, pp. 63 – 72.
[5] Grover, M. S., Lau, P. C. K., and Tanaka, W. H., “Reliability assessment of Special Protection Systems,” CIGRE paper 3A-11, presented at the CIGRE Symposium on Electric Power System Reliability, Montreal, Sept. 16-18, 1991.
[6] ISA-TR84.00.02-2002, The Instrumentation, Systems, and Automation Society (ISA), 2002.
[7] IEEE guide for general principles of reliability analysis of nuclear power generating station safety systems, ANSI/IEEE Std 352-1987.
[8] Ericson, C. A. II, and Andrews, J. D., "Fault tree and Markov analysis applied to various design complexities," in Proc. of the 18th International System Safety Conf. [Online]. Available: http://www.fault-tree.net
[9] IEEE guide for selecting and using reliability predictions based on IEEE 1413, IEEE Std 1413.1-2002.
[10] Mitra, J., Singh, C., “Monte Carlo simulation for reliability analysis of emergency and standby power systems,” Industry Applications Conference, 1995. Thirtieth IAS Annual Meeting, IAS '95., Conference Record of the 1995 IEEE, vol.3 , 8-12 Oct. 1995,pp. 2290 – 2295.
[11] Billinton, R., Sankarakrishnan, A., “A comparison of Monte Carlo simulation techniques for composite power system reliability assessment,” WESCANEX 95. Communications, Power, and Computing, Conference Proceedings, IEEE, Vol. 1, May 1995. pp. 145 – 150.
[12] Brombacher, A. C., and Knegtering, B., “Generating Micro Markov Models for Quantitative Safety and Reliability Assessment for Applications in the Process Industry, “ISA Expo 1998.
[13] Mingxiao, J., Wang, W., “Generalized decomposition method for complex systems,” Reliability and Maintainability, 2004 Annual Symposium - RAMS , 26-29 Jan. 2004, pp. 12 – 17.
[14] Ayyub B.M., Wilcox R.C., “Uncertainty modeling of data and uncertainty propagation for risk studies,” Uncertainty Modeling and Analysis, 2003, ISUMA 2003, Fourth International Symposium on , 21-24 Sept. 2003, pp. 184 – 191.
[15] Modarres, M., Kaminskiy, M. and Krivtsov, V., Reliability Engineering and Risk Analysis - A Practical Guide, New York, Basel: Marcel Dekker, Inc., 1999.
[16] Valette, A., Vanier, G., Huang, J. A. Wehenkel, L., and Harrison, S., “Application of data mining techniques for automat settings in emergency control at Hydro-Quebec,” IEEE Power Engineering Society General Meeting, Vol. 4, 13-17 July 2003, pp. 2037-2044.
[17] System Disturbances, 1986~1995, North American Electric Reliability Council.
[18] Hsiao, T. Y., Lu, C. N., and Liu, Y. H., ”Defense plan design in a longitudinal power system,” Proceedings of the 14th Power Systems Computation Conference (PSCC), Sevilla, 24-28 June 2002.
[19] 蕭純育, 李群, “特殊保護系統(SPS)簡介及應用於台電之經驗”, 電工通訊, 中國電機工程學會, 2004, Mar.(第一季), 第26-35頁.
[20] 周芳正, 蔡文達, 陳淞明, 林淳義, 鄭金龍, “於台電系統建造一特殊保護系統”, 第二十三屆電力工程研討會論文集, 民國91年, 第1016-1020頁.
[21] Hsiao, T. Y., Lu, C. N., Liu, Y. H., Chen, C. L. and Chang, B. S., ” Safety net design and implementation in taiwan power system,” IEE Proceedings of the 5th International Conference on Power System Management and Control (PSMC), 17-19 April 2002, pp. 41-46.
[22] 楊志仁, 張宏展, 蔡文達, 鄭金龍, “遙控跳脫興達電廠機組之特殊保護策略”, 第二十四屆電力工程研討會論文集, 民國92年, 第887-891頁.
[23] Mokhtari, A., Frey, H.C., and Danish, Evaluation of selected sensitivity analysis methods based upon applications to two food safety process risk models, Prepared by NC State University for U.S. Department of Agriculture, Washington, DC, September 2003.
[24] Reliability Data for Nuclear-Power Generating Stations, IEEE Std 500-1984.
[25] T. ROBERT M., the Reliability Data Handbook, Amer Society of Mechanical, November 3, 2004.