臺灣博碩士論文加值系統

本文以改良型烏鴉搜尋演算法作在N-1事故情形下最佳化配置UPFC(Unified Power Flow Controller)強化電力系統安全性。本文考慮系統發生發電機故障或斷線事故時，傳輸線路過載及匯流排電壓超出限制之情形，以加入UPFC改善並強化系統的安全性。在最佳化配置UPFC前，先對系統作發電機轉移因子及線路崩潰指標分析，透過此分析結果，挑選出對系統造成最嚴重衝擊的一部發電機組，與一條傳輸線作為系統發生意外事故之情形。接著利用改良型烏鴉搜尋演算法，在N-1事故情形下搜尋UPFC的最佳配置。為了證明改良型烏鴉搜尋演算法的有效性，將以IEEE 14-Bus系統及IEEE 30-Bus系統作測試，並與其他現有的方法比較電力系統的安全性情形及設置UPFC的成本。從結果可以看出本文提出的方法的確能有效地找到UPFC最佳配置，來強化系統的安全性。

The thesis presents an improved crow search algorithm (ICSA) to find out the optimal unified power flow controller (UPFC) placement for enhancing power system security under N-1 contingency condition. An UPFC is placed to enhance system security considering lines overload and bus voltage violations under a transmission line or a generator outage. Before placing an UPFC to system, the power system is performed generators shift factor and line collapse proximity index analyses and selected single transmission line or single generator as a contingency in the tests. Then an improved crow search algorithm is used to find out the optimal UPFC placement under N-1 contingency condition. To verify the effectiveness of ICSA, the tests are performed on IEEE 14-bus and IEEE 30-bus power systems and the results which are power system security and UPFC placement cost are compared with other methods. The results show that the proposed method can effectively find the optimal UPFC placement to enhance power system security.

目錄
摘要 i
Abstract ii
誌謝 iii
目錄 iv
表目錄 vi
圖目錄 viii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究方法與文獻回顧 1
1.3 論文大綱 4
第二章 問題描述 6
2.1 前言 6
2.2 在N-1事故情形下最佳化配置UPFC以強化電力系統安全性問題 6
2.2.1 UPFC之模型 6
2.2.2 系統安全性函數 8
2.2.3 同時考慮系統安全性與UPFC設置成本的函數 9
2.2.4 限制條件 10
第三章 研究方法與理論 13
3.1 前言 13
3.2 烏鴉搜尋演算法 13
3.3 烏鴉搜尋演算法的飛行方式 13
3.4 改良型烏鴉搜尋演算法 14
3.5 發電機之轉移因子 16
3.6 線路崩潰指標 17

第四章 以改良型烏鴉搜尋演算法作在N-1事故情形下最佳化配置UPFC以強化電力系統安全性問題 19
4.1 前言 19
4.2能量函數的建立 19
4.3以改良型烏鴉搜尋演算法作在N-1事故情形下最佳化配置UPFC以強化電力系統安全性問題之步驟 20
4.4 實例測試與分析24
4.4.1 IEEE 14-Bus 系統 24
4.4.1.1 考慮IEEE 14-Bus 系統發生發電機故障事故情形 28
4.4.1.2 考慮IEEE 14-Bus 系統發生傳輸線斷線事故情形 34
4.4.2IEEE 30-Bus 系統 39
4.4.2.1 考慮IEEE 30-Bus 系統發生發電機故障事故情形 47
4.4.2.2 考慮IEEE 30-Bus 系統發生傳輸線斷線事故情形 53
4.5 章節結論 60
第五章結論與未來展望 61
5.1 結論 61
5.2 未來展望 61
參考文獻 63

[1] H. I. Shaheen, G. I. Rashed, and S. J. Cheng “Optimal location and parameter setting of UPFC for enhancing power system security based on differential evolution algorithm,” International Journal of Electrical Power & Energy Systems, Vol. 33, pp. 94-105, January 2011.
[2] S. A. Taher, and M. K. Amooshahi, “New approach for optimal UPFC placement using hybrid immune algorithm in electric power systems,” International Journal of Electrical Power & Energy Systems, Vol. 43, pp. 899-909, December 2012.
[3] S. Galvani, M. T. Hagh, and M. B. B. Sharifian, “Unified power flow controller impact power system predictability,” IET Generation, Transmission & Distribution, Vol. 8, pp. 819-827, May 2014.
[4] A. Rajabi-Ghahnavieh, M. Fotuhi-Firuzabad, and M. Othman, “Optimal unified power flow controller application to enhance total transfer capability,” IET Generation, Transmission & Distribution, Vol. 9, pp. 358-368, March 2015.
[5] S. Kamel, F. Jurado, and J. A. P. Lopes, “Comparison of various UPFC models power flow control,” Electric Power Systems Reasearch, Vol. 121, pp. 243-251, April 2015.
[6] S. Kamel, F. Jurado, and R. Mihalic, “Advanced modeling of center-node unified power flow controller in NR load flow algorithm,” Electric Power Systems Research, Vol. 121, pp. 176-182, April 2015.
[7] B. V. Rao, and G. V. N. Kumar, “Optimal power flow by bat search algorithm for generation reallocation with unified power flow controller,” International Journal of Electrical Power & Energy Systems, Vol. 68, pp. 81-88, June 2015.
[8] S. Kamel, F. Jurado, Z. Chen, M. Abdel-Akher, and M. Ebeed, “Developed generalised unified power flow controller model in the Newton-Raphson power-flow analysis using combined mismatches method,” IET Generation, Transmission & Distribution, Vol.10, pp. 2177-2184, June 2016.
[9] P. Acharjee, “Optimal power flow with UPFC using security constrained self-adaptive differential evolutionary algorithm for restructured power system,” International Journal of Electrical Power & Energy Systems, Vol. 76, pp.69-81, March 2016.
[10] M. Moazzami, M. J. Morshed, and A. Fekih, “A new optimal unified flow controller placement and load shedding coordination approach using the hybrid imperialist competitive algorithm-pattern search method for voltage collapse prevention in power system,” International Journal of Electrical Power & Energy Systems, Vol. 79, pp. 263-274, July 2016.
[11] S. Dutta, P. Mukhopadhyay, P. K. Roy, and D. Nandi, “Unified power flow controller based reactive power dispatch using oppositional krill herd algorithm,” International Journal of Electrical Power & Energy Systems, Vol. 80, pp. 10-25, September 2016.
[12] B. V. Kumar, and N. V. Srikanth, “A hybrid approach for optimal location and capacity of UPFC to improve the dynamic stability of the power system,” Applied Soft Computing, Vol. 52, pp. 974-986, March 2017.
[13] S. Ravindra, C. V. Suresh, S. Sivanagaraju, and V. C. V. Reddy, “Power system security enhancement with unified power flow controller under multi event contingency conditions,” Ain Shams Engineering Journal, Vol. 8, pp. 9-28, March 2017.
[14] A. Askarzadeh, “A novel metaheuristic method for solving constrained engineering optimization problem:crow search algorithm,” Computers & Structures, Vol. 169, pp. 1-12, June 2016.
[15] M. Ghasemi, S. Ghavidel, M. M. Ghanbarian, M. Gharibzadeh, and A. A. Vahed, “Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm,” Energy, Vol. 78, pp. 276-
289, December 2014.
[16] M. A. Abido, “Optimal power flow using particle swarm optimization,” International Journal of Electrical Power & Energy Systems, Vol. 24, No. 7, pp. 563-571, October 2002.
[17] T. Niknam, M. R. Narimani, J. Aghaei, and R. Azizipanah-Abarghooee, “Improved particle swarm optimization for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index,” IET Generation, Transmission & Distribution, Vol. 6, No. 6, pp. 515-527, June 2012.
[18] A. A. Abou El Ela, M. A. Abido, and S. R. Spea, “Optimal power flow using differential evolution algorithm,” Electric Power Systems Research, Vol. 80, No. 7, pp. 878-885, July 2010.