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系統識別號 U0026-2007201517093100
論文名稱(中文) 應用仿生智能啟發技術於多目標電能調度與配電系統運轉效能提升
論文名稱(英文) Application of Bio-Inspired Intelligent Techniques to Multi-Objective Power Dispatch and Distribution System Operation Enhancement
校院名稱 成功大學
系所名稱(中) 電機工程學系
系所名稱(英) Department of Electrical Engineering
學年度 103
學期 2
出版年 104
研究生(中文) 戴德育
研究生(英文) Te-Yu Tai
學號 N26034435
學位類別 碩士
語文別 英文
論文頁數 79頁
口試委員 指導教授-黃世杰
召集委員-梁瑞勳
口試委員-鄧人豪
口試委員-吳元康
口試委員-蘇偉府
中文關鍵字 無效電力潮流調度  多目標最佳化  電壓不平衡  強化型海豚回聲定位演算法  混合型鳥類繁殖演算法 
英文關鍵字 reactive power dispatch  multi-objective optimization  voltage unbalance  enhanced dolphin echolocation algorithm  hybrid bird-mating optimization 
學科別分類
中文摘要 本論文之研究之主旨在於研發應用仿生智能啟發技術於多目標電能調度與配電系統運轉效能提升,並期經由所提之強化型海豚回聲定位演算法及混合型鳥類繁殖演算法等仿生技術之輔助,不僅提供輸電系統決策妥適之無效電力潮流調度,以達成降低線路損失、減少總負載電壓偏移量及增強電壓穩定度之目標外,並於配電系統中,有效降低電壓不平衡率,同時抑制太陽光電系統併網造成之電壓變動,以提升整體供電品質。而本論文為評估所提之仿生智能演算法對於提升輸電系統運轉效能之可行性,均已經由IEEE及實際系統予以模擬測試,同時利用其它方法針對相同系統架構測試比較,以驗證比較所提演算技術之計算效能,應有助於提供規劃人員參考依據,並俾於邁向優質供電電網之目標。
英文摘要 This thesis endeavors to apply the bio-inspired intelligent techniques to optimize the multi-objective power dispatch and enhance the distribution system operation. With the aid of both enhanced dolphin echolocation algorithm and hybrid bird-mating approach, not only the appropriate decision of reactive power dispatch can be attained to reduce the power losses, minimize the voltage deviation, increase the voltage stability, but also mitigate the voltage unbalance caused by the grid-connected PV systems so as to ensure a satisfactory supplying-power. To evaluate the effectiveness of these proposed methods, they were evaluated through IEEE sample systems and practical ones with comparisons to other methods. Test results gained from this thesis have confirmed the feasibility of the proposed methods, thereby serving as beneficial references for electric power engineers and paving a road towards a power grid of high-quality.
論文目次 摘要 I
Abstract II
誌謝 III
Contents IV
List of Tables VII
List of Figures VIII
Symbols and Abbreviations X
Chapter 1 Introduction 1
1.1 Background and Motivation 1
1.2 Literature Survey 2
1.3 Contribution of this Thesis 3
1.4 Organization of this Thesis 4
Chapter 2 Problem Description 7
2.1 Introduction 7
2.2 Reactive Power Dispatch Problem 7
2.2.1 Minimization of Real Power Losses 7
2.2.2 Improvement of Voltage Profile 8
2.2.3 Enhancement of Voltage Stability 8
2.2.4 Equality Constraints 9
2.2.5 Inequality Constraints 10
2.3 Phase-Connection Adjustment Problem 11
2.3.1 Distribution Transformers in Low-Voltage Network 11
2.3.2 Mathematical Model of Photovoltaic Penetration 13
2.3.3 Formulation of Objective Function 14
2.3.4 Constraints 17
2.4 Overview of Bio-Inspired Intelligent Techniques 18
2.5 Summary 19
Chapter 3 Application of Enhanced Dolphin Echolocation Algorithm to Multi-Objective Reactive Power Dispatch Optimization 21
3.1 Introduction 21
3.2 Overview of Enhanced Dolphin Echolocation Algorithm 22
3.2.1 Multi-Objective Optimization Concept 22
3.2.2 Mathematical Model Formulation of Dolphin Echolocation Algorithm 24
3.2.3 Enhanced Dolphin Echolocation Algorithm 25
3.3 Computation Procedures of Enhanced Dolphin Echolocation Algorithm 28
3.4 Numerical Studies of Enhanced Dolphin Echolocation Algorithm 31
3.4.1 IEEE 57-bus Power System 31
3.4.2 A 69 kV 43-bus Taiwan Power System 34
3.4.3 IEEE 118-bus Power System 39
3.4.4 IEEE 300-bus Power System 42
3.5 Summary 44
Chapter 4 A Hybrid Bird-Mating Optimization Approach Applied for Reinforced Phase-Connection of Distribution Transformers Considering Photovoltaic System Penetration 45
4.1 Introduction 45
4.2 Overview of Hybrid Bird-Mating Optimization Approach 46
4.2.1 Bird-Mating Optimization 46
4.2.2 Hybrid Bird-Mating Optimization Approach 48
4.3 Computation Procedures of Hybrid Bird-Mating Optimization Approach 49
4.4 Test Results of Hybrid Bird-Mating Optimization Approach 51
4.4.1 Industrial Feeder with 5% PV Penetration 53
4.4.2 Commercial Feeder with 10% PV Penetration 58
4.4.3 Residential Feeder with various PV Penetration 63
4.5 Summary 69
Chapter 5 Conclusions 70
5.1 Conclusions 70
5.2 Future Study 71
References 72
Biography 78
參考文獻 [1] 2014 Sustainability Reports of Taiwan Power Company [Online]. Available: http://www.taipower.com.tw/UpFile/File/CSR/2014.pdf
[2] F. Li, W. Qiao, H. Sun, H. Wan, J. Wang, Y. Xia, Z. Xu, and P. Zhang, “Smart Transmission Grid: Vision and Framework,” IEEE Transactions on Smart Grid, Vol. 1, No. 2, pp. 168-177, September 2010.
[3] M. T. Tsay and S. Y. Chan, “Improvement in System Unbalance and Loss Reduction of Distribution Feeders Using Transformer Phase Rearrangement and Load Diversity,” International Journal of Electrical Power & Energy Systems, Vol. 25, No. 5, pp. 395-401, June 2003.
[4] Y. S. Su, W. M. Lin, S. C. Chang, and M. T. Tsay, “Improving the System Unbalance and Losses of Distribution Feeders Based on Transformer Rearrangement,” TENCON 2004-2004 IEEE Region 10 Conference, Chiang Mai, Thailand, Vol. 3, pp. 448-451, 2004.
[5] H. C. Chin, R. J. Chung, Y. S. Su, and H. H. Sun, “Application of the Ant Colony System for Open Wye-Open Delta Transformer's Phase Sequence Adjustment,” TENCON 2004-2004 IEEE Region 10 Conference, Chiang Mai, Thailand, Vol. 3, pp. 432-435, 2004.
[6] M. Niu and Z. Xu, “Efficiency Ranking-Based Evolutionary Algorithm for Power System Planning and Operation,” IEEE Transactions on Power Systems, Vol. 29, No. 3, pp. 1437-1438, May 2014.
[7] C. M. Huang, S. J. Chen, Y. C. Huang, and H. T. Yang, “Comparative Study of Evolutionary Computation Methods for Active-Reactive Power Dispatch,” IET Generation, Transmission & Distribution, Vol. 6, No. 7, pp. 636-645, July 2012.
[8] L. Zhihuan, L. Yinhong, and D. Xianzhong, “Non-Dominated Sorting Genetic Algorithm-II for Robust Multi-Objective Optimal Reactive Power Dispatch,” IET Generation, Transmission & Distribution, Vol. 4, No. 9, pp. 1000-1008, September 2010.
[9] P. Subbaraj and P. N. Rajnarayanan, “Hybrid Particle Swarm Optimization Based Reactive Power Dispatch,” International Journal of Computer Applications, Vol. 1, No. 5, pp. 65-70, February 2010.
[10] T. Niknam, “A New Approach Based on Ant Colony Optimization for Daily Volt/Var Control in Distribution Networks Considering Distributed Generators,” Energy Conversion and Management, Vol. 49, No. 12, pp. 3417-3424, December 2008.
[11] S. Duman, Y. Sönmez, U. Güvenc, and N. Yörükeren, “Optimal Reactive Power Dispatch Using a Gravitational Search Algorithm,” IET Generation, Transmission & Distribution, Vol. 6, No. 6, pp. 563-576, June 2012.
[12] A. Khorsandi, A. Alimardani, B. Vahidi, and S. H. Hosseinian, “Hybrid Shuffled Frog Leaping Algorithm and Nelder-Mead Simplex Search for Optimal Reactive Power Dispatch,” IET Generation, Transmission & Distribution, Vol. 5, No. 2, pp. 249-256, February 2011.
[13] K. H. Chua, Y. S. Lim, P. Taylor, S. Morris, and J. Wong, “Energy Storage System for Mitigating Voltage Unbalance on Low-Voltage Networks with Photovoltaic Systems,” IEEE Transactions on Power Delivery, Vol. 27, No. 4, pp. 1783-1790, October 2012.
[14] K. Li, J. Liu, Z. Wang, and B. Wei, “Strategies and Operating Point Optimization of Statcom Control for Voltage Unbalance Mitigation in Three-Phase Three-Wire Systems,” IEEE Transactions on Power Delivery, Vol. 22, No. 1, pp. 413-422, January 2007.
[15] Y. Xu, L. M. Tolbert, J. D. Kueck, and D. T. Rizy, “Voltage and Current Unbalance Compensation Using a Static Var Compensator,” IET Power Electronics, Vol. 3, No. 6, pp. 977-988, November 2010.
[16] F. Shahnia, R. Majumder, A. Ghosh, G. Ledwich, and F. Zare, “Voltage Imbalance Analysis in Residential Low Voltage Distribution Networks with Rooftop PVs,” Electric Power Systems Research, Vol. 81, No. 9, pp. 1805-1814, September 2011.
[17] F. Shahnia, P. J. Wolfs, and A. Ghosh, “Voltage Unbalance Reduction in Low Voltage Feeders by Dynamic Switching of Residential Customers among Three Phases,” IEEE Transactions on Smart Grid, Vol. 5, No. 3, pp. 1318-1327, May 2014.
[18] M. W. Siti, D. V. Nicolae, A. A. Jimoh, and A. Ukil, “Reconfiguration and Load Balancing in the LV and MV Distribution Networks for Optimal Performance,” IEEE Transactions on Power Delivery, Vol. 22, No. 4, pp. 2534-2540, Octobor 2007.
[19] I. Ziari, G. Ledwich, A. Ghosh, and G. Platt, “Optimal Distribution Network Reinforcement Considering Load Growth, Line Loss, and Reliability,” IEEE Transactions on Power Systems, Vol. 28, No. 2, pp. 587-597, May 2013.
[20] A. Kaveh and N. Farhoudi, “A New Optimization Method: Dolphin Echolocation,” Advances in Engineering Software, Vol. 59, pp. 53-70, May 2013.
[21] A. Askarzadeh, “Bird Mating Optimizer: An Optimization Algorithm Inspired by Bird Mating Strategies,” Communications in Nonlinear Science and Numerical Simulation, Vol. 19, No. 4, pp. 1213-1228, April 2014.
[22] E. K. P. Chong and S. H. Zak, An Introduction to Optimization, 4th edition, Hoboken, New Jersey, U.S.A., Wiley, 2013.
[23] H. Saadat, Power System Analysis, 2nd edition, New York, U.S.A., McGraw-Hill, 2004.
[24] W. H. Kersting, Distribution System Modeling and Analysis, 2nd edition, Boca Raton, Florida, U.S.A., CRC Press, 2006.
[25] R. C. Dugan. Open Distribution System Simulator (OpenDSS) [Online]. Available: http://sourceforge.net/projects/electricdss/
[26] C. Y. Chung, C. H. Liang, K. P. Wong, and X. Z. Duan, “Hybrid Algorithm of Differential Evolution and Evolutionary Programming for Optimal Reactive Power Flow,” IET Generation, Transmission & Distribution, Vol. 4, No. 1, pp. 84-93, January 2010.
[27] Technical Manual of Overhead Line Design for Distribution Systems, Taiwan Power Company, 2009.
[28] Interconnection Guideline of Renewable Energy, Taiwan Power Company, 2009.
[29] K. M. Passino, Biomimicry for Optimization, Control, and Automation, New York, U.S.A., Springer, 2004.
[30] A. P. Engelbrecht, Computational Intelligence: An Introduction, 2nd edition, Hoboken, New Jersey, U.S.A., Wiley, 2007.
[31] R. L. Haupt and S. E. Haupt, Practical Genetic Algorithms, 2nd edition, Hoboken, New Jersey, U.S.A., Wiley, 2004.
[32] K. Y. Lee, Y. M. Park, and J. L. Ortiz, “A United Approach to Optimal Real and Reactive Power Dispatch,” IEEE Transactions on Power Apparatus and Systems, Vol. PAS-104, No. 5, pp. 1147-1153, May 1985.
[33] K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, pp. 182-197, April 2002.
[34] M. Clerc, Particle Swarm Optimization, Hoboken, New Jersey, U.S.A., Wiley, 2010.
[35] IEEE 57-Bus Test System [Online]. Available:
http://www.ee.washington.edu/research/pstca/pf57/pg_tca57bus.htm
[36] C. Dai, W. Chen, Y. Zhu, and X. Zhang, “Seeker Optimization Algorithm for Optimal Reactive Power Dispatch,” IEEE Transactions on Power Systems, Vol. 24, No. 3, pp. 1218-1231, August 2009.
[37] IEEE 118-Bus Test System [Online]. Available:
http://www.ee.washington.edu/research/pstca/pf118/pg_tca118bus.htm
[38] IEEE 300-Bus Test System [Online]. Available:
http://www.ee.washington.edu/research/pstca/pf300/pg_tca300bus.htm
[39] C. Y. Chang, J. S. Yu, and C. S. Chen, “Effects of Open-Wye/Open-Delta Transformers on the Operation of Distribution Systems,” Electric Power Systems Research, Vol. 10, No. 3, pp. 167-174, May 1986.
[40] M. A. de Armas and G. Garcia, “Selection of Asymmetrical Transformers Banks with Emphasis in Losses and Efficiency,” IEEE Latin America Transactions, Vol. 8, No. 6, pp. 678-684, December 2010.
[41] S. Santoso and R. C. Dugan, “Experiences with the New Open-Wye / Open-Delta Transformer Test Cases for Distribution System Analysis,” IEEE Power Engineering Society General Meeting, San Francisco, California, U.S.A., Vol. 1, pp. 884-889, 2005.
[42] Million Solar Rooftop PVs Office [Online]. Available: https://mrpv.org.tw/
[43] B. N. Alajmi, K. H. Ahmed, S. J. Finney, and B. W. Williams, “Fuzzy-Logic-Control Approach of a Modified Hill-Climbing Method for Maximum Power Point in Microgrid Standalone Photovoltaic System,” IEEE Transactions on Power Electronics, Vol. 26, No. 4, pp. 1022-1030, April 2011.
[44] Installed Capacity and System Load of Taiwan Power Company Electricity Grid [Online]. Available:
http://web3.moeaboe.gov.tw/ECW/populace/web_book/WebReports.aspx?book=M_CH&menu_id=142
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