近年來由於二氧化碳的排放所造成的全球暖化的問題，逐漸的受到世界各國的重視，在京都議定書中也開始訂立多項策略，來減輕與減緩因排放二氧化碳所引起的溫室效應。在全球暖化之議題上，電力部門的碳排放佔有舉足輕重的地位，因此，如何在電力運轉過程中降低二氧化碳排放量為本文之主要研究課題。

本文提出於台灣電力系統與碳交易市場結合之情況下，並以台電之最大化利潤為目標，並應用粒子群最佳化演算法(Particle Swarm Optimization, PSO) 並結合最佳化電力潮流(Optimal Power Flow, OPF)之計算求解二十四小時動態經濟調度問題。在求解動態經濟調度問題時，除了考慮供需平衡、機組發電量限制、發電機升載率與降載率限制之外，還包含負載潮流、匯流排電壓限制與傳輸線容量限制。另本文提出輸電業者加入碳交易市場並運用靜態同步串聯補償器(Static Synchronous Series Compensator, SSSC)裝設於各線路，以達到控制系統之電力潮流，產生對污染排放量的影響。於考量交易市場的情況下，藉由裝設靜態同步串聯補償器的影響，並參考二十四小時電力與碳之價格與需量預測資料，經由買賣電力與碳權額度以及代輸費用計價的交易行為，進而達到獲取最大利潤之目標，作為是否投入交易市場之依據。為了改善粒子群最佳化演算法陷入局部最佳解之問題，本文另提出使用混合基因概念之具時變性質粒子群演算法，具有跳脫局部最佳解之能力，使其能快速且精確獲得整體最佳解。

In recent years the global warming due to the increasing Carbon Oxide emission has attracted much attention. The Kyoto Protocol also has initiated many mitigation strategies to alleviate the global warming due to excessive carbon emission. The mass amount of carbon emissions and power plans are known to be highly related. How to reduce the carbon emission in the process of power production has become a major human issue and is the focus of this project.

This thesis proposed the application of Particle Swarm Optimization (PSO) algorithm and Optimal Power Flow (OPF) to solve the dynamic economic dispatch (DED) problem for 24 hours with maximum profit integrating the carbon trading market with the power system in Taiwan. The DED problem must satisfy the constraints of the load demand, generating limits, ramp rate limits, and also the limits of power flow, buses voltage and transmission line capacity. The other objective of this thesis is the participation of electric transmission in carbon trading market with the employment of the Static Synchronous Series Compensator (SSSC) to control the power flow. The Taiwan Power Company (TPC) can get the maximum profit with installed SSSC from the power and carbon trading, and can also assess the need of participating in the trading market or not. To avoid the local optimality problem, this thesis proposed the utilization of the Genetic Algorithm Hybrid Time-Varying Particle Swarm Optimization (GAHTVPSO) method, which can quickly reach the optimal solution with a better performance and accuracy.

摘 要 i
Abstract ii
目 錄 iii
圖 次 v
表 次 viii

第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究方法與目的 2
1.3 論文架構 3

第二章 碳交易與電力市場 5
2.1 碳交易市場 5
2.1.1 碳交易市場架構 5
2.1.2 台灣碳排放交易制度分析 7
2.2 電力市場 9
2.2.1 電力市場架構 9
2.2.2 台灣電業自由化架構之探討 12
2.2.3 代輸費用 16

第三章 整合靜態同步串聯補償器於負載潮流模型 20
3.1 靜態同步串聯補償器模型應用於負載潮流之設計 21
3.1.1 電流注入法負載潮流模型 21
3.1.2 SSSC電壓源型轉換器數學模型 29
3.2 SSSC線路裝設之原則與設計 38
3.3 台灣電力系統案例設計 42
3.3.1 台電於碳交易市場最大利潤之數學模型 42
3.3.2 台電污染排放數學模型 49

第四章 改良型粒子群最佳化演算法之設計 53
4.1 前言 53
4.2 改良型粒子群最佳化演算法 59
4.2.1 具時變性質加速係數粒子群最佳化演算法之設計 59
4.2.2 混合基因概念之具時變性質粒子群最佳化演算法之設計 60

第五章 系統測試與結果分析 64
5.1 改良型粒子群最佳化演算法之收斂測試 71
5.2 案例測試 74
5.2.1 案例一：台灣電力系統以年為基礎的日平均負載測試 74
5.2.2 案例二：台灣電力系統春季負載測試 80
5.2.3 案例三：台灣電力系統夏季負載測試 85
5.2.4 案例四：台灣電力系統秋季負載測試 90
5.2.5 案例五：台灣電力系統冬季負載測試 95
5.2.6 案例六：台灣電力系統全年測試 100

第六章 結論與未來發展方向 106
6.1 結論 106
6.2 未來發展方向 107

參考文獻 108
附錄 114

[1] 鄭富升，“可行式粒子演算法解含限制條件之最佳化問題”，中華民國第三十屆電力研討會，民國九十八年十一月。
[2] 李元輝，“我國產業未來參與碳排放交易之方向”，碩士論文，國立中山大學電機系研究所，民國九十八年六月。
[3] 林奇章、林坤讓，“結合碳交易以價格為導向之機組排程研究”，臺灣期刊論文，臺灣人纖工業會訊第六十一卷，pp. 33-38，民國九十七年十月。
[4] “台灣電力公司”，http://www.taipower.com.tw/
[5] G. D. Galanos, C. I. Hatziadoniu, and X-j. Cheng “Advanced Static Compensator for Flexible AC Transmission,” IEEE Transactions on Power Systems, Vol. 8, No. 1, pp. 113-121, 1993.
[6] I. Papic, P. zunko, D. Povh, and M. Weinhold, “Basic Control of Unifie Power Flow Controller,” IEEE Transactions on Power Systems, Vol. 12, No. 4, pp. 1734-1739, 1997.
[7] C. B. Somuah, and N. Khunaizi, “Application of linear programming redispatch technique to dynamic generation allocation,” IEEE Transactions on Power Systems, Vol. 5, No. 1, pp. 20-26, 1990.
[8] Delson, K. Jerome, and S.M. Shahidehpour, “Linear programming applications to power system economics, planning and operations,” IEEE Transactions on Power Systems, Vol. 7, No. 3, pp. 1155-1163, 1992.
[9] B. Stott, and J.L. Marinho, “Linear Programming for Power-System Network Security Applications,” IEEE Transactions on Power Apparatus and Systems, Vol. PAS-98, No. 3, pp. 837-848, 1979.
[10] F. Li, R. Morgan, and D. Williams, “Towards more cost saving under stricter ramping rate constraints of dynamic economic dispatch problems - a genetic based approach,” Proceedings of the IEE Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, Glasgow, pp. 221-225, 1997.
[11] J.F. Frenzel, “Genetic algorithms,” IEEE Transactions on Potentials, Vol. 12, No. 3, pp. 21-24, 1993.
[12] S.A. Kazarlis, A.G. Bakirtzis, and V. Petridis, “A genetic algorithm solution to the unit commitment problem,” IEEE Transactions on Power Apparatus and Systems, Vol. 11, No. 1, pp. 83-92, 1996.
[13] R. H. Liang, “A neural-based redispatch approach to dynamic generation allocation,” IEEE Transactions on Power Systems, Vol. 14, No. 4, pp. 1388-1393, 1999.
[14] Arturo S. Bretas, and Arun G. Phadke, “Artificial neural networks in power system restoration,” IEEE Transactions on Power Delivery, Vol. 18, No. 4, pp. 1181-1186, 2003.
[15] M. L. Kothari, Ravi Segal and Bhushan K.Ghodki “Adaptive conventional power system stabilizer based on artificial neural network,” IEEE Transactions on Power Electronics, Drives and Energy Systems, Vol. 2, pp. 1072-1077, 1996.
[16] P. Attaviriyanupap, H. Kita, E. Tanaka, and J. Hasegawa, “A hybrid EP and SQP for dynamic economic dispatch with nonsmooth fuel cost function,” IEEE Transactions on Power Systems, Vol. 17, No. 2, pp. 411-416, 2002.
[17] I. Perez Abril, and J.A.G. Quintero, “VAr compensation by sequential quadratic programming,” IEEE Transactions on Power Systems, Vol. 18, No. 1, pp. 36-41, 2003.
[18] Yongfei Ma, and Xianmin Wang “Application of Sequential Quadratic Programming Algorithm based on region search method in reactive power optimization,” IEEE Transactions on Electrical and Electronics Engineerings, pp. 1-5, 2006.
[19] W. Ongsakul, and N. Ruangpayoongsak, “Constrained dynamic economic dispatch by simulated annealing/genetic algorithms,” Proceedings of the International Conference on 22nd IEEE Power Engineering Society, Sydney, pp. 207-212, 2001.
[20] Jing Ye, and Fang Zong Wang, “A refined plant growth simulation algorithm for distribution network reconfiguration,” IEEE International Conference on Intelligent Computing and Intelligent Systems, 2009. ICIS 2009, Vol. 1, pp. 357-361, 2009.
[21] L. Barriga, and R. Ronngren, and Rassul Ayani, “Benchmarking parallel simulation algorithms,” IEEE First International Conference on Algorithms and Architectures for Parallel Processing, Vol. 2, pp. 611-620, 1995.
[22] 黃宗煌、李堅明，“台灣如何因應碳交易市場的來臨?”，環境經濟學，西元2008年一月。
[23] 黃琮暉，“ASP技術於電力交易與競爭系統研究”，碩士論文，國立中山大學電機工程研究所，民國九十二年六月。
[24] 陳麗芬，“電力自由化與獨立電廠營運之探討”，碩士論文，國立中山大學財務管理研究所，民國八十九年六月。
[25] A. K. David, “Dispatch methodologies for open access transmission systems,” IEEE Transactions on Power Systems, Vol.13, No. 1, pp. 46-53, February. 1998.
[26] 國家政策研究基金會，“我國電業自由化架構之研討討”，
http://old.npf.org.tw/Symposium/s90/900428-TE-1.htm.
[27] 王京明，”台灣電力系統電力代輸之研究(期末報告)”，財團法人中華經濟研究院，民國八十六年六月。
[28] D. Shirmohamadi, et al, “Evaluation of transmission network capacity use for wheeling transactions,” IEEE Transactions on Power Systems, Vol. 4, No. 4, pp. 1405-1413, Nov. 1989.
[29] J. Bialek, “Allocation of transmission supplementary charge to real and reactive loads,” IEEE Transactions on Power Systems, Vol. 13, No. 3, pp. 749-754, Aug. 1998.
[30] E. Vaahedi, H. M. Z. El-Din, W. W.Price, “Dynamic load modeling in large scale stability studies,” IEEE Transactions on Power Systems, Vol.3, Aug. 1988, pp.1039-1045.
[31] IEEE Task Force on Load Representation for Dynamic Performance, “Load Representation for Dynamic Performance Analysis,” IEEE Transactions on Power Systems, Vol.8, May 1993, pp.472-482.
[32] Ying-Yi Hong, “Impacts of load models on solutions of Newton optimal power flow,” 1993 IEEE Region 10 Conference on Computer, Communication, Control and Power Engineering, Vol. 5, 19-21 Oct. 1993, pp. 398-401.
[33] W. S. Kao, C. T. Huang and C. Y. Chiou, "Dynamic load modeling in Taipower system stability studies," IEEE Transactions on Power Systems, vol. 10, Issue:2, May 1995, pp.907 – 914.
[34] Kuo-Hsiung Tseng, Wen-Shiow Kao, Jia-Renn Lin, “Load model effects on distance relay settings,” IEEE Transactions on Power Delivery, vol.18, Issue: 4, Oct. 2003, pp.1140- 1146.
[35] 曾國雄、黃逢佑、高秀文，“電力系統負載模型參數之研究”，臺北科技大學學報第四十之一期，民國九十五年十一月。
[36] J. Carpentiers, “Contribution a. ‘l’etude du dispatching economique,” Bull. Soc. Francaise Elect., vol. 3, pp. 431-447, 1962.
[37] M. Huneault, and F. D. Galiana, “A Survey of The Optimal Power Flow Literature,” IEEE Trans. On Power Systems, vol. 6, no. 2, pp. 762-770, May 1991.
[38] G. Verbic, and C. A. Canizares, “Probabilistic Optimal Power Flow in Electricity Markets Based on A Two-Point Estimate Method,” IEEE Trans. On Power Systems, vol. 21, no. 4, pp. 1883-1893, Nov. 2006.
[39] A. J. Wood, and B. F. Wollenberg, “Power Generation Operation and Control,” John Wiley & Sons, Inc., 1996.
[40] 黃琮暉、黃仲麒、林冠禎，“應用混合型人工智慧演算法於最佳化電力潮流之研究”，遠東學報第二十六卷第二期。
[41] W. M. Lin and J. H. Teng, “Phase-Decoupled Load Flow Method for Radial and Weakly-Mesh Distribution Networks,” IEE Proceedings-Generation, Transmission and Distribution, Vol. 143, No. 1, pp. 39-42, January 1996.
[42] W. M. Lin, Yuh-Sheng Su, Hong-Chan Chin, and J. H. Teng, “Three-Phase Unbalanced Distribution Power Flow Solutions With Minimum Data Preparation,” IEEE Transactions on Power Systems, Vol. 14, No. 3, pp. 1178-1183, Aug. 1999.
[43] 詹東昇，“應用以電流為基礎的網路模型於輸電系統負載潮流之研究”，碩士論文，國立中山大學電機系研究所，民國八十八年六月。
[44] 吳杰康、秦礪寒、胡文霞、寧琳，“含靜止同步串聯補償器的電力系統電壓穩定性奇異值分析法及指標計算”，電網技術第三十三卷第五期，pp. 6-10, 2009.
[45] 葛俊、童陸園、耿俊成，“TCSC 抑制次同步諧振的機理研究及其參數設計”，中國電機工程學報第二十二卷第六期，pp. 25-29, 2002.
[46] 郭春林、童陸園，“多機系統中可控串補(TCSC)抑制功率振盪的研究”，中國電機工程學報第二十四卷第六期，pp. 1-6, 2004.
[47] 姜旭、肖湘寧，“級聯結構的小步長建模”，高電壓技術第三十二卷第十期，pp. 1-3, 2006.
[48] 吳孟哲，“應用SSSC於電力市場之碳交易評估”，碩士論文，國立中山大學電機系研究所，民國一百年六月。
[49] W. L. Fang and H. W. Ngan, “Optimising location of unified power flow controllers using the method of augmented Lagrange multipliers,” IEE Proceedings - Generation, Transmission and Distribution, Vol. 146, No. 5, September 1999.
[50] R. Eberhart, and J. Kennedy, “ A new optimizer using particle swarm theory,” Proceedings of the Sixth International Symposium on Micro Machine and Human Science, pp.39-43, Japan, Oct. 1995.
[51] 李維平、王雅賢、江正文，“粒子群最佳化演算法改良之研究”，科學與工程技術期刊第四卷第二期，pp.51-62, 2008.
[52] F. S. Cheng, J. S. Tu, C. H. Lv and M. T. Tsay, “A Generalized Regression Neural Network for Solving Economic Dispatch Problem,” ICEE for the 21st Century with focus on Sustainability and Reliability, pp. 113, Jul. 2007.
[53] A. Ratnaweera, S. k. Halgamuge and H. C. Watson, “Self-Organizing Hierarchical Particle Swarm Optimization with Time-Varying acceleration coefficients,” IEEE Transactions on Evolutionary Computation, Vol. 8, No. 3, pp. 240-255, Jun. 2004.
[54] “The EU Emissions Trading System,”
http://ec.europa.eu/clima/policies/ets/index_en.htm
[55] 廖基宏，“應用電力追蹤探討電力代輸成本”，碩士論文，國立中正大學電機工程研究所，民國八十九年七月。