Responsive image
博碩士論文 etd-0704115-174900 詳細資訊
Title page for etd-0704115-174900
論文名稱
Title
台灣電力系統十年安全調度規劃與備載裕度之研究
Study of the Ten-Year Security Dispatch Planning and Reserve Margin for Taiwan Power System
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
162
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2015-07-08
繳交日期
Date of Submission
2015-08-05
關鍵字
Keywords
備載容量率、動態經濟調度、屆齡除役、具時變性質加速係數粒子群最佳化演算法、邊際成本
Dynamic Economic Dispatch, Particle Swarm Optimization with Time-Varying Acceleration Coefficients, Marginal Cost, Compulsory Retirement, Percent Operating Reserve
統計
Statistics
本論文已被瀏覽 5689 次,被下載 231
The thesis/dissertation has been browsed 5689 times, has been downloaded 231 times.
中文摘要
西元2011年3月11日,日本宮城縣東方外海發生規模9.0矩震級地震,除了強大的地震波襲擊東日本各城市以外,由地震所引發之海嘯更是對各沿海城市帶來更加嚴重的破壞。其中,日本東京電力公司所屬的福島核電廠也因為海嘯引發核外洩事件,核電使用安全議題再次引發全球關注。鄰近的我國同樣無法置身事外,國人陸續發起街頭運動,訴求核一、核二與核三廠立即或屆齡停機除役,同時必須用更嚴格的標準檢視興建中的龍門電廠(核四)。政府經過不斷的開會協商之後決議未來核能能源政策方針訂為「既有核能發電廠在預定除役日期到達後不予以延役;核四廠暫停施工,直到在確保在安全基礎上才會予以商轉」。而台電公司亦因應此政策下訂定了無核四版本之未來電源開發計劃,以供應未來可能持續成長的電力負載。

本文提出以改良式粒子群最佳化演算法-結合模糊控制器之具時變性質加速係數粒子群最佳化演算法(FCHTVAC-PSO)用以求解台灣電力系統24小時各時段發電成本最小化之動態經濟調度問題。除了考慮各時段供需平衡、各機組發電量限制、發電機升載率與降載率以外,亦考量負載潮流、匯流排電壓限制以及傳輸線容量等限制。本論文研究將著重於探討每部核能發電機組屆齡除役時,該年度24小時各時段最小發電成本動態經濟調度狀況,包含其結果對系統備載容量率、夏季與非夏季各時段每度電邊際成本等衝擊,作為未來電力系統規劃與電價制定主管機關之參考依據。
Abstract
The 9.0 magnitude earthquake occurred on 11 March 2011 in the north-western Pacific Ocean, Not only the strong seismic waves but also tsunami caused destructive damage to the coastal city in eastern Japan,. The nuclear power safety became a big issues because of nuclear leakage incident. People started to attend street campaign to appeal for compulsory retirement of Nuclear Power Generators. At the same time , using more strict standard to examine the construction of the Long-Men (4th nuclear power plants). After negotiation meeting, Republic of China government announced 1st , 2nd and 3rd nuclear plant will be retired when arriving compulsory retirement date. And 4th nuclear power plant should be suspended the construction until safety measurement is finished. According to the policies, Taipower company proposed the power planning without nuclear power to supply increasing electric power load.

This thesis proposed the application of Fuzzy Controller Hybrid Time-Varying Acceleration Coefficients Particle Swarm Optimization (FCHTVAC-PSO) to solve the dynamic economic dispatch (DED) problem over the entire 24-hour period with minimum cost each hour period for Taiwan power system. The DED problem must satisfy the constraints of the load demand, generating limits, and also the limit of power flow, buses voltage and transmission line capacity. This thesis proposed a research focused on the minimum cost DED result with compulsory retirement of every nuclear power generators and variation of percent operating reserve and marginal cost.
目次 Table of Contents
目 錄
論文審定書 ..................................................................................................................... i
致謝 ................................................................................................................................ii
摘要 .............................................................................................................................. iii
Abstract ......................................................................................................................... iv
目錄 ................................................................................................................................ v
圖次 ..............................................................................................................................vii
表次 ................................................................................................................................ x
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 台灣電力系統發電結構與電價發展現況分析 ............................................ 5
2.1 台灣電力公司之起源 .................................................................................... 5
2.2 台灣電力系統現今發電結構概況 ................................................................ 6
2.2.1 火力發電概況 ........................................................................................ 6
2.2.2 核能發電概況 ........................................................................................ 8
2.2.3 再生能源等發電概況 .......................................................................... 10
2.3 台灣電力系統電價發展現況分析 .............................................................. 11
第三章 台灣電力系統動態經濟調度模型之設計 .................................................. 15
3.1 等效電流注入法求解電力潮流問題 .......................................................... 15
3.1.1 負載匯流排模型推導 .......................................................................... 16
3.1.2 電壓控制匯流排模型推導 .................................................................. 20
3.2 台灣電力系統24 小時動態經濟調度模型與模擬案例設計 .................... 24
3.2.1 台電系統24 小時動態經濟調度數學模型之設計 ............................ 24
vi
3.2.2 模擬案例設計 ...................................................................................... 30
第四章 結合模糊控制器之具時變性質加速係數粒子群最佳化演算法 .............. 34
4.1 模糊理論 ...................................................................................................... 34
4.1.1 模糊集合與歸屬函數 .......................................................................... 35
4.1.2 模糊推論引擎與解模糊化 .................................................................. 36
4.2 粒子群最佳化演算法 .................................................................................. 38
4.3 具時變性質加速係數粒子群最佳化演算法 .............................................. 42
4.4 結合模糊控制器之具時變性質加速係數粒子群最佳化演算法設計 ...... 44
4.4.1 模糊控制器設計 .................................................................................. 44
4.4.2 結合模糊控制器之具時變性質加速係數粒子群最佳化演算法 ...... 49
第五章 系統測試與案例分析 .................................................................................. 51
5.1 改良型粒子群最佳化演算法之收斂測試 .................................................. 55
5.2 台灣電力系統24 小時動態經濟調度案例分析 ........................................ 61
5.2.1 案例一:民國104 年現況分析 .......................................................... 61
5.2.2 案例二:民國107 年核一廠第一機組除役分析 .............................. 68
5.2.3 案例三:民國108 年核一廠第二機組除役分析 .............................. 75
5.2.4 案例四:民國110 年核二廠第一機組除役分析 .............................. 82
5.2.5 案例五:民國112 年核二廠第二機組除役分析 .............................. 88
5.2.6 案例六:民國113 年核三廠第一機組除役分析 .............................. 94
5.2.7 案例七:民國114 年核三廠第二機組除役分析 ............................ 100
第六章 結論與未來研究方向 ................................................................................ 107
6.1 結論 ............................................................................................................ 107
6.2 未來研究方向 ............................................................................................ 109
參考文獻 .................................................................................................................... 110
附錄 ............................................................................................................................ 115
參考文獻 References
[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98年11月。
[2] “地震國,不該發展核電”,全國廢核行動平台,民國102年3月。
[3] 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.
[4] J. Yuryevich, and K. P. Wong, “Evolutionary Programming Based Optimal Power Flow Algorithm, ”IEEE Transactions on Power Systems, Vol. 14, pp.1245-1250, 1999.
[5] 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.
[6] 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.
[7] J.F. Frenzel, “Genetic algorithms,” IEEE Transactions on Potentials, Vol. 12, No. 3, pp. 21-24, 1993.
[8] 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.
[9] 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.
[10] A. S. Bretas, and A. G. Phadke, “Artificial neural networks in power system restoration,” IEEE Transactions on Power Delivery, Vol. 18, No. 4, pp. 1181-1186, 2003.
[11] M. L. Kothari, R. Segal and B. 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.
[12] 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.
[13] 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.
[14] 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.
[15] 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.
[16] 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.
[17] 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.
[18] “台灣電力公司歷史與發展”,台灣電力公司,民國104年4月。
[19] “火力發電簡介”,台灣電力公司,民國104年4月。
[20] “核電廠基本資料”,台灣電力公司,民國104年4月。
[21] “我國再生能源發電現況”,台灣電力公司,民國104年4月。
[22] “促進電價合理化”,台灣電力公司,民國104年4月。
[23] “6月1日起夏月電價將比去年同期低”,經濟部能源局,民國104年5月。
[24] H. Saadat, “Power System Analysis,” McGraw-Hill, Inc., 2/e, 1996.
[25] J. Carpentier, “Contribution a. ‘1’etude du dispatching economique,” Bull. Soc. Francaise Elect., Vol. 3, pp. 431-447, 1962.
[26] W. M. Lin and J. H. Teng, “Distribution Fast-Decoupled State Estimation by Measurement Pairing,” IEE Proceedings, Generation, Transmission, and Distribution, Vol. 143, No. 1, pp. 43-48, Jan.1996.
[27] W. M. Lin, C. H. Huang and T. S. Zhan, “A Hybrid Current-Power Optimal Power Flow Technique,” IEEE Transactions on Power Systems, Vol. 23, No. 1, pp. 177-185, Feb. 2008.
[28] W. M. Lin, Y. S. Su, H. C. Chin and J. H. Teng, “Three-Phase Unbalanced Distribution Power Flow Solutions with Minimum Data Preparation,” IEEE Transactions on Power Systems, Vol. 143, pp. 1179-1183, Aug. 1999.
[29] W. M. Lin and S. J. Chen, “Bid-Based Dynamic Economic Dispatch with An Efficient Interior Point Method,” International Journal of EPES, Vol. 24, pp. 51-57, Apr. 2002.
[30] 林惠民,“自由化下電力和備轉容量之最佳調度以及節點現貨價格計算之研究”,國科會計畫成果報告,NSC89-TPC-7-110-006,2000。
[31] 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”,國立中山大學電機研究所碩士論文,民國88年6月。
[32] L.A. Zadeh, “Fuzzy Sets,” Information and Control, Vol. 8, pp. 339-353, 1965.
[33] L.A. Zadeh, “The concept of a linguistic variable and its applications to approximate reasoning-I,” Information Sciences, Vol 8, No. 3, pp. 199-249, 1975.
[34] L.A. Zadeh, “The concept of a linguistic variable and its applications to approximate reasoning-II,” Information Sciences, Vol. 8, No. 4, pp. 301-357, 1975.
[35] 吳曉莉,林哲輝,“MATLAB輔助模糊系統設計”,西安電子科技大學出版社,2002。
[36] R. C. Eberhart and J. Kennedy, “A new optimizer using particle swarm theory,” Proceedings of the Sixth International Symposium on Micromachine and Human Science, Nagoya, Japan. pp. 39-43, 1995.
[37] J. Kennedy and R. C. Eberhart “Particle swarm optimization,” Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ. pp. 1942-1948, 1995.
[38] Y. Shi and R. Eberhart, “Empirical Study of Particle Swarm Optimization,” Proc. IEEE Evol. Comput, Vol. 3, pp. 69-73, 1999.
[39] 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.
[40] 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.
[41] K. T. Chaturvedi, M. Pandit and L. Srivastava, “Self-Organizing Hierarchical 102 Particle Swarm Optimization for Nonconvex Economic Dispatch,” IEEE Transactions on Power System, Vol. 23, Iss. 3, pp. 1079-1087, Aug. 2008.
電子全文 Fulltext
本電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
論文使用權限 Thesis access permission:自定論文開放時間 user define
開放時間 Available:
校內 Campus: 已公開 available
校外 Off-campus: 已公開 available


紙本論文 Printed copies
紙本論文的公開資訊在102學年度以後相對較為完整。如果需要查詢101學年度以前的紙本論文公開資訊,請聯繫圖資處紙本論文服務櫃台。如有不便之處敬請見諒。
開放時間 available 已公開 available

QR Code