因應全球電力需求日益增加與地球暖化等因素，太陽能與風力發電系統之使用日趨普及。不確定性與不可控制的再生能源發電滲透率過高將對系統帶來一定程度之衝擊，進而影響系統供電安全與可靠度。一個適切的備轉容量評估與機組排程策略除有利於維持系統運轉的供需平衡外，亦可在營運成本最小的情形下因應再生能源發電對系統的衝擊。
本文提出應用於日前規劃之機組經濟調度與調頻備轉排程之最佳化策略，可用於高滲透率太陽能與風力發電併網之系統，以降低系統頻率變動使其符合系統規範，同時減少系統的營運成本，其中包含供給電力與躉購備轉容量之成本。所提方法主要透過快速傅立葉轉換，以分析總負載減去再生能源發電量之淨負載曲線與機組排程量間之動態差值，並將時域之資訊轉換為頻域中所對應之需求量，進而區分不同反應時間所需之備轉容量。本文亦提出一個機組能量與容量的混合最佳化排程演算法，以同時考量電力系統運轉的經濟效益與安全，並藉以決定不同特性之備轉容量需求分配。文中亦依據分析結果討論系統是否需要啟動需量反應機制或儲能系統作為備轉容量的來源以彌補系統穩定運轉需求。
配合台灣能源轉型政策，本文採用台電系統現在與未來預估再生能源發電、負載資料及系統相關參數，以分析不同情境下之備轉容量與排程結果，並探討未來擴大推廣再生能源發電對電力系統各級調頻輔助服務需求之影響。最佳化方法整合PSS○RE電力系統模擬軟體，以驗證所得解之可行性。本文所提策略與分析結果可協助台電公司或其他電力調度營運單位安排備轉容量，並作為系統長程開發規劃之參考。

In response to the global issues of increasing power demand and global warming, photovoltaic (PV) and wind turbine (WT) systems are becoming increasingly popular. A high penetration rate of uncertain and uncontrollable renewable energy sources (RES) will exert a certain effect on these systems that can compromise power supply security and reliability. A suitable reserve capacity evaluation and unit commitment (UC) strategy is conducive to maintaining a balance between supply and demand and can lessen the impact of power generation by RES to the system with the smallest operating cost.
This thesis proposes a day-ahead optimization strategy of economic dispatch (ED) and frequency regulation reserve (FRR) allocation that can be used in systems with high PV and WT penetration to reduce frequency variation. This strategy ensures compliance with system regulations while reducing operating costs including the cost of power supply and reserve purchasing. The proposed method analyzes the dynamic difference between the net-load curve, which is obtained by the subtraction of RES power output from the total load, and the unit commitment result by using Fast Fourier Transform (FFT). Time-domain signals are converted into corresponding requirements in the frequency spectrum to distinguish different response times. This thesis also proposes a joint optimization scheduling algorithm for unit energy and capacity to simultaneously consider the system’s economic efficiency and safety and obtain the allocated reserve to each supplier in different reserve classes. Moreover, based on the analysis results, this paper discusses whether the system requires a demand response (DR) or an energy storage system (ESS) as a reserve supplier that can fulfil the requirement for stable system operation.
In line with Taiwan’s energy transition policy, this thesis conducts a simulation based on current and future predictions of renewable energy generation, load data, and parameter setting in the Taipower system to analyze reserve capacity requirements and schedule results in various scenarios. The impact of frequency regulation reserve capacity (FRRC) requirements in different classes under future expansion of RES power generation is also explored. Power System Simulator for Engineering (PSS○RE) software is integrated into the optimization process to verify the feasibility of the solution. The proposed strategy and analysis results can assist Taipower or other system operators in properly arranging their FRRC and can serve as a reference for long-term system development.

[1] Y. Fu, M. Shahidehpour, and Z. Li, “Security-Constrained Unit Commitment with AC Constraints,” IEEE Transactions on Power Systems, Vol. 20, no. 3, Aug. 2005.
[2] E. Gil, J. Toro, and G. Gutiérrez-Alcaraz, “Day-Ahead Reserve Scheduling Approaches under Wind Uncertainty,” IEEE Power & Energy Society General Meeting, Chicago, IL, 2017, pp. 1-5.
[3] C. Rahmann, A. Heinemann, and R. Torres, “Quantifying Operating Reserves with Wind Power: Towards Probabilistic–Dynamic Approaches,” IET Generation, Transmission & Distribution, vol. 10, no. 2, pp. 366-373, 2016.
[4] E. Ela, B. Kirby, E. Lannoye, M. Milligan, D. Flynn, B. Zavadill, and M. O'Malley, “Evolution of Operating Reserve Determination in Wind Power Integration Studies,” IEEE PES General Meeting, Minneapolis, MN, 2010, pp. 1-8.
[5] X. Yan, B. Francois, and D. Abbes, “Operating Power Reserve Quantification Through PV Generation Uncertainty Analysis of a Microgrid,” IEEE Eindhoven PowerTech, Eindhoven, 2015, pp. 1-6.
[6] I. Krad, D. W. Gao, E. Ela, E. Ibanez, and H. Wu, “Analysis of Operating Reserve Demand Curves in Power System Operations in The Presence of Variable Generation,” IET Renewable Power Generation, vol. 11, no. 7, pp. 959-965, 2017.
[7] E. S. E. Sharif, M. U. T. Chowdhury, and M. Moniruzzaman, “An Overview of Frequency Control as a Criterion of Power System Reliability and International Survey of Determining Operating Reserve,” American Journal of Modern Energy, vol. 3, pp. 101-114, Oct. 2017.
[8] D. Brett and K. W. Chin, “A Comparison of Deterministic and Probabilistic Methods for Indoor Localization,” Journal of Systems and Software, vol. 84, 2011.
[9] J. F. Prada, “The Value of Reliability in Power Systems Pricing Operating Reserves”, Energy lab, MIT, Jun. 1999.
[10] H. F. Boroujeni, M. Eghtedari, M. Abdollahi, and E. Behzadipour “Calculation of Generation System Reliability Index: Loss of Load Probability,” Life Science Journal, vol. 9, no. 4, Dec. 2012.
[11] M. S. Rao and V. N. Naikan, “Review of Simulation Approaches in Reliability and Availability Modeling,” International Journal of Performability Engineering, vol. 12, no. 4, July 2016.
[12] L. M. Carvalho,” Using Evolutionary Swarms (EPSO) in Power System Reliability Indices Calculation,” U. PORTO, 2013.
[13] A. Al-Alawi, M. Nagle, and J. Zhu, “Utilizing Reliability Indices to Study Generation Adequacy,” IEEE Transmission and Distribution Conference and Exposition, New Orleans, LA, USA, 2010, pp. 1-5.
[14] M. S. E. Sharif, M. U. T. Chowdhury, M. J. Ferdous, M. Moniruzzaman, “An Efficient Method for Power System Frequency Control and Optimal Reserve Determination Considering Probabilistic Loss-of-Load Expectation Risk Index,” IEEE Electrical Information and Communication Technology, 2017.
[15] I. K. Odinakaeze, “Assessment of Spinning Reserve Requirements in a Deregulated System,” USASK, Canada, 2010.
[16] R. M. Johnson, “Integrated Resource Planning with PLEXOS,” World Bank Thirsty Energy, Morocco, 2014.
[17] M. Ortega-Vazquez and D. Kirschen, “Optimizing the Spinning Reserve Requirements Using a Cost/Benefit Analysis,” IEEE Transactions on Power Systems, vol. 22, no. 1, pp. 24-33, Feb. 2007.
[18] V. Knap, S. K. Chaudhary, D. I. Stroe, M. Swierczynski, B. I. Craciun, and R. Teodorescu, “Sizing of an Energy Storage System for Grid Inertial Response and Primary Frequency Reserve,” IEEE Transactions on Power Systems, vol. 31, no. 5, pp. 3447-3456, Sept. 2016.
[19] J. Frunt, W. L. Kling, and P. F. Ribeiro, “Wavelet Decomposition for Power Balancing Analysis,” IEEE Transactions on Power Delivery, vol. 26, no. 3, pp. 1608-1614, July 2011.
[20] J. Frunt, W. L. Kling, and J. M. A. Myrzik, “Classification of Reserve Capacity in Future Power Systems,” International Conference on the European Energy Market, Leuven, 2009, pp. 1-6.
[21] J. Frunt, W. L. Kling, and P. P. J. van den Bosch, “Classification and Quantification of Reserve Requirements for Balancing”, Electric Power Systems Research, vol. 80, 2010.
[22] M. Milligan, H. Holttinen, E. Lannoye, D. Flynn, M. O’Malley, N. Miller, P. B. Eriksen, A. Gøttig, B. Rawn, M. Gibescu, E. G. Lázaro, A. Robitaille, and I. Kamwa, “Operating Reserves and Wind Power Integration: An International Comparison,” Annual International Workshop on Large-Scale Integration of Wind Power into Power Systems, Canada, Oct. 2010.
[23] F. L. Alvarado, “Spectral Analysis of Energy-Constrained Reserves,” Proceedings of the 35th Annual Hawaii International Conference on System Sciences, 2002, pp. 749-756.
[24] Z. Song, L. Goel, and P. Wang, “Risk Based Spinning Reserve Allocation in Deregulated Power Systems,” IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings, vol. 2, 2004, pp. 491-494.
[25] Z. Song, L. Goel, and P. Wang, “Optimal Spinning Reserve Allocation in Deregulated Power Systems,” IEE Proceedings - Generation, Transmission and Distribution, vol. 152, no. 4, pp. 483-488, July 2005.
[26] A. Bhatt, A. Shrivastava, M. Pandit, and H. M. Dubey, “Dynamic Scheduling of Operating Energy and Reserve in Electricity Market with Ramp Rate Constraints,” International Conference on Recent Advances and Innovations in Engineering, Jaipur, 2014, pp. 1-6.
[27] X. You, H. Wu, J. Zhang, S. Jin, Y. Ding, and P. Siano, “Optimal Day-Ahead and Intra-Day Scheduling of Energy and Operating Reserve Considering Fluctuating Wind Power,” IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe, Milan, 2017, pp. 1-6.
[28] E. N. Azadani, S. H. Hosseinian, and B. Moradzadeh, “Generation and Reserve Dispatch in a Competitive Market Using Constrained Particle Swarm Optimization,” International Journal of Electrical Power & Energy Systems, vol. 32, Jan. 2010.
[29] V. Rostampour, O. ter Haa, and T. Keviczky, “Tractable Reserve Scheduling in AC Power Systems with Uncertain Wind Power Generation,” IEEE 56th Annual Conference on Decision and Control, Melbourne, VIC, 2017, pp. 2647-2654.
[30] C. L. Chen, “Optimal Generation and Reserve Dispatch in a Multi-Area Competitive Market Using a Hybrid Direct Search Method,” Energy Convers Manage, vol. 46, pp. 2856-2872, Nov. 2005.
[31] X. Ma and D. Sun, “Energy and Ancillary Service Dispatch in a Competitive Pool,” IEEE Power Engineering Review, vol. 18, no. 1, pp. 54-56, Jan. 1998.
[32] A. G. Bakirtzis, “Joint Energy and Reserve Dispatch in a Competitive Pool Using Lagrangian Relaxation,” IEEE Power Engineering Review, vol. 18, no. 11, pp. 60-62, Nov. 1998.
[33] X. Ma, D. Sun, and K. Cheung, “Energy and Reserve Dispatch in a Multi-Zone Electricity Market,” IEEE Transactions on Power Systems, vol. 14, no. 3, pp. 913-919, Aug. 1999.
[34] F. Wen and A. K. David, “Coordination of Bidding Strategies in Day-Ahead Energy and Spinning Reserve Markets,” International Journal of Electrical Power & Energy Systems, vol. 24, pp. 251-261, May 2002.
[35] D. J. Swider, “Simultaneous Bidding in Day-Ahead Auctions for Spot Energy and Power Systems Reserve,” International Journal of Electrical Power & Energy Systems, vol. 29, pp. 470-479, July 2007.
[36] E. Gil, J. Toro, and G. Gutiérrez-Alcaraz, “Day-Ahead Reserve Scheduling Approaches under Wind Uncertainty,” IEEE Power & Energy Society General Meeting, Chicago, IL, 2017, pp. 1-5.
[37] B. D. Hari Kiran and M. S. Kumari, “Optimal Generation Scheduling with Operating Reserves Including Wind Uncertainties,” International Conference on Smart Electric Grid, Guntur, 2014, pp. 1-6.
[38] N. Gong, X. Luo, and D. Chen, “Bi-Level Two-Stage Stochastic SCUC for ISO Day-Ahead Scheduling Considering Uncertain Wind Power and Demand Response,” The Journal of Engineering, vol. 2017, no. 13, pp. 2549-2554, 2017.
[39] V. K. Tumuluru, Z. Huang, and D. H. K. Tsang, “Integrating Price Responsive Demand into the Unit Commitment Problem,” IEEE Transactions on Smart Grid, vol. 5, no. 6, pp. 2757-2765, Nov. 2014.
[40] S. H. Madaeni and R. Sioshansi, “The Impacts of Stochastic Programming and Demand Response on Wind Integration,” Energy System, vol. 4, pp. 109-124, June 2013.
[41] X. Liu, B. Wang and L. I. Yang, “Stochastic Unit Commitment Model for high Wind Power Integration Considering Demand Side Resources,” Proceedings of the Chinese Society for Electrical Engineering, 2015, pp. 3714–3723.
[42] P. Fortenbacher, A. Ulbig, S. Koch, and G. Andersson, “Grid-Constrained Optimal Predictive Power Dispatch in Large Multi-Level Power Systems with Renewable Energy Sources, and Storage Devices,” IEEE PES Innovative Smart Grid Technologies, Europe, Istanbul, pp. 1-6, 2014.
[43] T. Zheng and E. Litvinov, “Contingency-Based Zonal Reserve Modeling and Pricing in a Co-Optimized Energy and Reserve Market,” IEEE Transactions on Power Systems, vol. 23, no. 2, pp. 277-286, May 2008.
[44] J. M. Morales, A. J. Conejo, and J. Perez-Ruiz, “Economic Valuation of Reserves in Power Systems with High Penetration of Wind Power,” IEEE Power & Energy Society General Meeting, Calgary, Canada, July 2009, pp. 1-1.
[45] K. Bruninx, E. Delarue, and W. D’haeseleer, The Cost of Wind Power Forecast Errors in the Belgian Power System, Apr. 2014. [Online]. Available: https://www.mech.kuleuven.be/en/tme/research/energy_environment/Pdf/wpen2014-10.pdf. [Accessed 1 May 2018]
[46] 台灣電力股份有限公司官方網站, 台灣電力公司. [Online]. Available: http://www.taipower.com.tw. [Accessed 1 May 2018]
[47] 電源開發處, 106 年長期電源開發方案, 台灣電力公司, 2018.
[48] 綠能科技產學研整合服務網, 台灣儲能系統產業推動聯盟成軍, 2018. [Online]. Available: http://www.getis.tw/News/Detail/16. [Accessed 1 May 2018]
[49] 台灣電力公司, 需量反應負載管理措施, 2017. [Online]. Available: https://www.taipower.com.tw/upload/135/2017110817314269395.pdf. [Accessed 1 May 2018]
[50] M. Milligan, H. Holttinen, E. Lannoye, D. Flynn, M. O’Malley, N. Miller, P. B. Eriksen, A. Gøttig, B. Rawn, M. Gibescu, E. G. Lázaro, A. Robitaille, and I. Kamwa, Operating Reserves and Wind Power Integration: An International Comparison, Oct. 2010. [Online]. Available: http://www.nrel.gov/docs/fy11osti/49019.pdf. [Accessed 1 May 2018]
[51] EnerNex Corporation, Eastern Wind Integration and Transmission Study, Feb. 2011. [Online]. Available: https://www.nrel.gov/docs/fy11osti/47078.pdf. [Accessed 1 May 2018]
[52] GE Energy, Western Wind and Solar Integration Study, May 2010. [Online]. Available: https://www.nrel.gov/docs/fy10osti/47434.pdf. [Accessed 1 May 2018]
[53] M. Cartwright,“ Fourier Methods for Mathematicians, Scientists and Engineers,“ Ellis Horwood Limited, pp. 77-220, 1990, May 1990.
[54] R. Christie, Power System Test Case Archive, Aug. 1993. [Online]. Available: https://www2.ee.washington.edu/research/pstca/pf30/pg_tca30bus.htm. [Accessed 1 May 2018]
[55] Ellis, Grid Operations and High Penetration PV, Nov. 2010. [Online]. Available: https://www1.eere.energy.gov/solar/pdfs/2010ulw_ellis.pdf. [Accessed 1 May 2018]