隨著科技的進步與經濟的發展，對電的需求也逐漸變大。電力系統的穩定不但關乎人們的生活，也進而影響企業的生產製造與發展。不穩定的系統將可能致使企業蒙受損失。由此可見，供電議題對現今社會而言的重要性也越來越高。
台灣現在用以評估缺電的指標為「備用容量率」，雖然備用容量率的概念一定程度上解釋了電力系統的安全與穩定，然其定義僅針對確定性之數值做分析。在再生能源發展快速的時代，供需的不確定性都較往常為高，備用容量率已無法完全反應系統的可靠與穩定。同時，在新型態的電力系統，備用容量率的設定亦不斷遭受挑戰；因此，本研究參考國際間之作法，導入機率模型及蒙地卡羅模擬的方式估算期望缺電時數，再與備用容量率做換算，進行模擬和可靠度分析。
本研究運用電力系統資訊，考慮在不同的能源配比情境下，在可調度情況時如何進行調度會使期望缺電時數最小、系統損失降到最低。相較以往「備用容量率」此評估缺電指標，本研究運用機率和統計的方式更能考量供電風險及不確定性因子，期望透過這樣的方式，不但更能反映風險，也可以提供能源調度上的參考及分析電力系統可靠度，進而輔助管理者進行決策。

The significance of power supply issue becomes greater to modern society. The reliability of electricity system not only affects our life, but also has great influence on the manufacturing process flow and development of company. In Taiwan, when it comes to the indicator of evaluating power outage, there is only “Percent Reserve Margin” as our main indicator. However, it was a controversial indicator with respect to estimating power outage in the past. As a result, we followed international power company’s method, applying probability method and Monte Carlo simulation method to estimate loss of load expectation which is an indicator for evaluating power outage in general. An empirical study is conducted in this paper to show the performance of the proposed method is promising and our methodology is useful in risk control under several circumstances. We can not only find out the best energy allocation for national power system but also provide a good indicator for decision makers via proposed method.

Bagen, B., Moura, J., & Jefferies, K. (2014, July). Probabilistic reliability assessment of North American Electric Power Systems. In Probabilistic Methods Applied to Power Systems (PMAPS), 2014 International Conference on (pp. 1-6). IEEE.
Billinton, R., & Bai, G. (2004). Generating capacity adequacy associated with wind energy. IEEE transactions on energy conversion, 19(3), 641-646.
Billinton, R., Chen, H., & Ghajar, R. (1996). A sequential simulation technique for adequacy evaluation of generating systems including wind energy. IEEE Transactions on Energy Conversion, 11(4), 728-734.
Booth, R. R. (1972). Power system simulation model based on probability analysis. IEEE Transactions on Power Apparatus and Systems, (1), 62-69.
Boßmann, T., & Staffell, I. (2015). The shape of future electricity demand: exploring load curves in 2050s Germany and Britain. Energy, 90, 1317-1333.
Castro, M. (2017). Assessing the risk profile to security of supply in the electricity market of Great Britain. Energy Policy, 111, 148-156.
Cherif, H., & Belhadj, J. (2014). Energy output estimation of hybrid Wind-Photovoltaic power system using statistical distributions. Journal of Electrical Systems, 10(2).
Energy Market Authority. (2016). Singapore electricity market outlook. Retrieved from https://www.ema.gov.sg/cmsmedia/Singapore%20Electricity%20Market%20Outlook%20Final.pdf
Ettoumi, F. Y., Mefti, A., Adane, A., & Bouroubi, M. Y. (2002). Statistical analysis of solar measurements in Algeria using beta distributions. Renewable Energy, 26(1), 47-67.
Georgilakis, P. S., & Katsigiannis, Y. A. (2009). Reliability and economic evaluation of small autonomous power systems containing only renewable energy sources. Renewable Energy, 34(1), 65-70.
Hasche, B., Keane, A., & O'Malley, M. (2011). Capacity value of wind power, calculation, and data requirements: the Irish power system case. IEEE Transactions on Power Systems, 26(1), 420-430.
Karki, R., & Billinton, R. (2001). Reliability/cost implications of PV and wind energy utilization in small isolated power systems. IEEE Transactions on Energy Conversion, 16(4), 368-373.
Karki, R., Hu, P., & Billinton, R. (2006). A simplified wind power generation model for reliability evaluation. IEEE transactions on Energy conversion, 21(2), 533-540.
Karki, R., Hu, P., & Billinton, R. (2010). Reliability evaluation considering wind and hydro power coordination. IEEE Transactions on Power Systems, 25(2), 685-693.
Kayal, P., & Chanda, C. K. (2015). Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network. Renewable Energy, 75, 173-186.
Korea Power Exchange. (2010). The 5th Basic Plan for Long-term Electricity Supply and Demand. Retrieved from file:///D:/Downloads/The%205th%20BPE%25282010-2024%2529.pdf
Li, W. (2015). Framework of probabilistic power system planning. CSEE Journal of Power and Energy Systems, 1(1), 1-8.
North American Electric Reliability Corporation. (2008). Reliability assessment guidebook. Retrieved from http://www.nerc.com/docs/pc/ragtf/Reliability_Assessment_%20Guidebook%20v1.2%20031909.pdf
Prognos. (2017). Flexibility in thermal power plants. Retrieved from https://www.agora-energiewende.de/fileadmin/Projekte/2017/Flexibility_in_thermal_plants/115_flexibility-report-WEB.pdf
University of Wisconsin-Madison. (2013). Active Power Ramp Rates. Retrieved from https://neos-guide.org/sites/default/files/ramp_rates.pdf
Vijayamohanan Pillai, N. (2014). Loss of Load Probability of a Power System. J Fundam Renewable Energy Appl, 5(149), 2.
Wu, L., Shahidehpour, M., & Li, T. (2008). Cost of reliability analysis based on stochastic unit commitment. IEEE Transactions on Power Systems, 23(3), 1364-1374.
Zhao, S., & Singh, C. (2017). Studying the Reliability Implications of Line Switching Operations. IEEE Transactions on Power Systems, 32(6), 4614-4625.
台灣電力公司（2017）。簡明月報。取自https://www.taipower.com.tw/upload/43/2017110314375313066.pdf
林家豪、許世哲、陳世麟、呂嘉容、盧豐彰、楊豐碩、林章平、陳隆武、孫建平、周錦雲(2010)。台電系統規模之合理備用容量率。台灣電力公司委託中原大學研究計畫。
郭瑾瑋、周裕豐、洪明龍、劉子衙 (2015)。應用臺灣TIMES模型進行我國長期電力供需規劃。臺灣能源期刊，2(4)，363-382。
鄭文吉 (2012)。漫談蒙地卡羅的原理及其應用。高雄區農業改良場研究彙報，23(1)，26-41。