未來幾年內大量的離岸風機將併入台灣電網中，在既有的電網規劃下可能產生線路壅塞的問題，導致離岸風能削減的現象。為找出2021、2025潛在的壅塞線路，本文根據聚類機組排程模型來模擬不同時期各機組的運轉情形，搭配預測的再生能源發電、負載輸入至電網中進行電力潮流分析，並以敏感度分析來分辨壅塞線路與離岸風機發電之關聯性，從中歸納出離岸風能削減的計算方法。最終採用蒙地卡羅法產生不同壅塞線路的再生能源發電削減率與發電削減風險率，此法同時考慮了故障、負載及再生能源發電的不確定性，能夠有效評估2021、2025整年離岸風能削減之情形，有助於後續在電網規劃或經濟效益之分析。

In the next few years, the high penetration of offshore wind energy may result in network congestion in Taiwan, which will lead to wind power curtailment. In order to determine the potential line congestion in 2021 and 2025, in this research, the clustered unit commitment model is used to simulate mixed generation. The resultant generation profile is further used to carry out a power flow analysis of a line flow sensitivity study. The sensitivity index between the congested line and the wind integration point is then utilized to estimate the wind curtailment and degree of risk. Finally, the Monte Carlo method is adopted to investigate the annual renewable curtailment and risk for 2021 and 2025, respectively, which takes the uncertainties of forced line outage, load and renewable generation into account. The evaluation results will aid with transmission planning and renewable investments in the future.

[1] 中華民國行政院經濟部能源局, 107年度全國電力資源供需報告. 2018.
[2] Alam, M.S., et al., High-Level Penetration of Renewable Energy Sources Into Grid Utility: Challenges and Solutions. IEEE Access, 2020. 8: p. 190277-190299.
[3] Li, Y., et al. Practices and Challenge on Planning with Large-scale Renewable Energy Grid Integration. in 2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2). 2019.
[4] Erlich, I., et al., Offshore Wind Power Generation Technologies. Proceedings of the IEEE, 2013. 101(4): p. 891-905.
[5] Colmenar-Santos, A., et al., Offshore wind energy: A review of the current status, challenges and future development in Spain. Renewable and Sustainable Energy Reviews, 2016. 64: p. 1-18.
[6] Burke, D.J. and M.J.O. Malley, Factors Influencing Wind Energy Curtailment. IEEE Transactions on Sustainable Energy, 2011. 2(2): p. 185-193.
[7] Bird, L., et al., Wind and solar energy curtailment: A review of international experience. Renewable and Sustainable Energy Reviews, 2016. 65: p. 577-586.
[8] 陳昱霖, 應用機組聚類概念實現中期機組排程. 2019, 國立成功大學.
[9] Senjyu, T., et al., A Fast Technique for Unit Commitment by Genetic Algorithm Based on Unit Integration. IFAC Proceedings Volumes, 2003. 36(20): p. 479-484.
[10] Sen, S. and D.P. Kothari, An Equivalencing Technique for Solving the Large-Scale Thermal Unit Commitment Problem, in The Next Generation of Electric Power Unit Commitment Models, B.F. Hobbs, et al., Editors. 2001, Springer US: Boston, MA. p. 211-225.
[11] Palmintier, B.S. and M.D. Webster, Heterogeneous Unit Clustering for Efficient Operational Flexibility Modeling. IEEE Transactions on Power Systems, 2014. 29(3): p. 1089-1098.
[12] Meus, J., K. Poncelet, and E. Delarue, Applicability of a Clustered Unit Commitment Model in Power System Modeling. IEEE Transactions on Power Systems, 2018. 33(2): p. 2195-2204.
[13] Corporation, G.D. Gurobi 9. Available from: https://www.gams.com/latest/docs/S_GUROBI.html.
[14] Alemany, J., et al., Short-Term Scheduling of Combined Cycle Units Using Mixed Integer Linear Programming Solution. Energy and Power Engineering, 2013. 05(02): p. 161-170.
[15] 台灣電力股份有限公司. 台電長期電源開發規劃. Available from: https://www.taipower.com.tw/tc/page.aspx?mid=212&cid=122&cchk=260a432c-fc0e-47e0-a90e-2bc0cc52cb61.
[16] 張穎朝, 氣渦輪機組運轉維護研討會. 2019: 台灣電力股份有限公司.
[17] Company, G.E. 7HA gas turbine. Available from: https://www.ge.com/gas-power/products/gas-turbines/7ha.
[18] Wood, A. and B. Wollenberg, Power generation, operation, and control. 2012. 632.
[19] 台灣電力股份有限公司, 台灣電力股份有限公司輸電系統規劃準則. 2020.
[20] Zhu, J., D. Hwang, and A. Sadjadpour. The Implementation of Alleviating Overload in Energy Markets. in 2007 IEEE Power Engineering Society General Meeting. 2007.
[21] Tejada-Arango, D.A., P. Sánchez-Martın, and A. Ramos, Security Constrained Unit Commitment Using Line Outage Distribution Factors. IEEE Transactions on Power Systems, 2018. 33(1): p. 329-337.
[22] Billinton, R. and R.N. Allan, Generating capacity—basic probability methods, in Reliability Evaluation of Power Systems, R. Billinton and R.N. Allan, Editors. 1996, Springer US: Boston, MA. p. 18-82.
[23] Wu, L., M. Shahidehpour, and T. Li, Stochastic Security-Constrained Unit Commitment. IEEE Transactions on Power Systems, 2007. 22(2): p. 800-811.
[24] Ekisheva, S. and H. Gugel. North American AC circuit outage rates and durations in assessment of transmission system reliability and availability. in 2015 IEEE Power & Energy Society General Meeting. 2015.
[25] Koval, et al. Modeling Severe Weather Related High Voltage Transmission Line Forced Outages. in 2005/2006 IEEE/PES Transmission and Distribution Conference and Exhibition. 2006.
[26] Glasserman, P., Generating Random Numbers and Random Variables, in Monte Carlo Methods in Financial Engineering, P. Glasserman, Editor. 2003, Springer New York: New York, NY. p. 39-77.
[27] Koval, D.O. and A.A. Chowdhury. Assessment of transmission line common mode, station originated and fault types forced outage rates. in Conference Record 2009 IEEE Industrial & Commercial Power Systems Technical Conference. 2009.