應用免疫演算法於輸電系統最佳化無效功率調度

An Immune Algorithm for Optimal Reactive Power Dispatch of Transmission Systems

夏倬彥(Cho-Yen Hsia)

指導教授 ： 陳昭榮

國立臺北科技大學/電資學院/電機工程系研究所/碩士(2008年)

https://doi.org/10.6841/NTUT.2008.00052

摘要

對提高電力系統的品質、效率及安全性而言，無效功率調度問題是一個很重要的因素，而最佳化無效功率調度是屬於多目標之最佳化函數問題。本論文提出應用免疫演算法，並使用電力潮流分析，對輸電系統做最佳化的無效功率調度，使輸電系統中各負載匯流排電壓在合理的範圍與最小化輸電線有效功率損失，避免因負載改變時或因偶發事故而造成電壓崩潰的現象。免疫演算法係基於人體的適應性免疫的行為所發展出來的最佳化演算法，本方法將目標函數和限制條件視為抗原，而所有的可行解則為抗體，利用免疫系統內的記憶細胞的功能，將較佳的抗體保留至下一代，這樣可以避免好的抗體因為交配與突變的運算而消失。本論文也利用免疫系統中抑制細胞的特性來抑制相似度高的抗體，這樣可以增加抗體的雜異度也能避免太早收斂而侷限於區域最佳解中。使用IEEE 30-bus系統與簡化台電系統作測試，並且將調度結果與基因演算法、蟻拓演算法及螞蟻系統比較。經由驗證與測試可知，本論文所提出的免疫演算法可以有效降低輸電線有效功率損失，期望能夠協助調度人員作更精確、經濟且安全的調度。

關鍵字

免疫演算法 ； 記憶細胞 ； 抑制細胞 ； 無效功率調度

並列摘要

For raising power system quality, efficiency and safety, reactive power dispatch is an important cause and accordingly adopted to solve problems. This thesis proposes to apply Immune Algorithm to facilitate the multi-objective optimal reactive power dispatch for transmission systems. The aims are achieving three major purposes: regulating voltage magnitude of load buses within a reasonable region, reducing real power loss of transmission line, and avoid the risk of voltage collapse owing to load demand change or contingencies.
Immune Algorithm developed from the adaptive immune response in human body, the objective function and constraints are expressed as antigen and all feasible solutions are expressed as antibody. Use the memory cell function in immune system to keep the superior antibodies to next generation also avoid destroyed by crossover and mutation, equally use the suppressor cell function to restrain the high affinity antibodies that can increase diversity of antibodies to not falling into the local optimal solution.
The thesis simulates the proposed method on IEEE 30-bus power system and simple Taipower system. The dispatch solutions are then compared to their counterparts obtained by Genetic Algorithm, Ant Colony System and Ant System respectively. Results show that the proposed method works best in reducing real power loss and securing voltage stability. The proposed method can therefore be expected to render dispatch safer, faster, and cheaper.

並列關鍵字

Immune Algorithm ； Memory Cell ； Suppressor Cell ； Reactive Power Dispatch

參考文獻

[1]K. Iba, “Reactive Power Optimization by Genetic Algorithm,” IEEE Trans. on Power Systems, Vol. 9, No. 2, 1994, pp. 685-692.

[3]A. J. Urdaneta, J. F. Gomez, E. Sorrentino, L. Flores and R. Diaz, “A Hybrid Genetic Algorithm for Optimal Reactive Power Planning Based Upon Successive Linear Programming,” IEEE Trans. on Power Systems, Vol. 14, No. 4, 1999, pp. 1292-1298.

[4]W. Yan, F. Liu, C. Y. Chung and K. P. Wong, “A Hybrid Genetic Algorithm–Interior Point Method for Optimal Reactive Power Flow,” IEEE Trans. on Power Systems, Vol. 21, No. 3, 2006, pp. 1163-1169.

[5]G. Krost and G. A. Bakare, “A Genetic Algorithm Based Approach for Improvement in Voltage Profile and Real Power Loss Minimization,” Proceedings of the 1999 conference on Power Tech, Budapest, Hungary, 1999.

[6]Q. H. Wu and J. T. Ma, “Power System Optimal Reactive Power Dispatch Using Evolutionary Programming,” IEEE Trans. on Power Systems, Vol. 10, No. 3, 1995, pp.1243-1249.