Optimal variable-gain neural network-based UPFC Controller by means of differential evolution algorithm

International Review of Electrical Engineering

Volumn 5, Issue 3, 2010, Pages 1069-1077

  Jazebi, S ^a   Baghaee, H R ^a   Gharehpetian, G B ^a  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Artificial neural networks; Differential evolution algorithm; Inter area oscillations; Power system stability; UPFC

Indexed keywords

EID: 79956146994     PISSN: 18276660     EISSN: 25332244     Source Type: Journal    
DOI: None     Document Type: Article

References (34)

1. N.G. Hingorani, L. Gyugyi, Understanding FACTS: concepts and technology of flexible AC transmission systems. (Wiley-IEEE Press, 1999).
2. IEEE Power Engineering Society and CIGRE, FACTS overview (IEEE publication, No. 95 TP 108, 1995).
3. Y.H. Song, A.T. Johns, Flexible AC Transmission Systems (IEE Press, 1999).
4. G. Radman, R. S. Raje, Power flow model/calculation for power systems with multiple FACTS controllers, EPSR, vol. 77, 2007, pp. 1521-1531.
5. W. Fang, H. W. Ngan, Enhancing small signal power system stability by coordinating unified power flow controller with power system stabilizer, EPSR, vol. 65, 2003, pp. 91-99,.
6. A. Kazemi, V. Vahidinasab, A. Mosallanejad, Study of STATCOM and UPFC Controllers for Voltage Stability Evaluated by Saddle-Node Bifurcation Analysis, ~PECon 2006~, 2006, pp. 191-195.
7. S. Krishna, K. R. Padiyar, Discrete control of unified power flow controller for stability improvement, EPSR, vol. 75, 2005, pp. 178-189.
8. J. S. K. Leung, D. J. Hill, Y. Ni, Global power system control using generator excitation, PSS, FACTS devices and capacitor switching, IJEPES, vol. 27, 2005, pp. 448-464.
9. M. A. Abido, A.T. Al-Awami, Y. L. Abdel-Magid, Analysis and Design of UPFC Damping Stabilizers for Power System Stability Enhancement, IEEE International Symposium on Industrial Electronics, vol. 3, 2006, pp. 2040-2045.
10. th Annual Conference of the IEEE, vol. 2, 2003, pp. 1540-1545.
11. S. O. Faried, A. A. Eldamaty, Damping power system oscillations using a genetic algorithm based unified power flow controller, ECE, vol. 1, 2004, pp. 65-68.
12. S. Panda, N. P. Padhy, R. N. Patel, Application of Genetic Algorithm for FACTS based Controller Design, Int. J. computer, information, systems science and engineering, vol.1, 2007, pp. 40-47.
13. A. T. Al-Awami, Y. L. Abdel-Magid, M. A. Abido, A particleswarm-based approach of power system stability enhancement with unified power flow controller, Int. J EPES, vol. 29, 2007, pp. 251-259.
14. M. Tripathy, S. Mishra, G. K. Venayagamoorthy, Bacteria Foraging, A New Tool for Simultaneous Robust Design of UPFC Controllers, Neural Networks, IJCNN, 2006, pp. 2274-2280.
15. T. K. MOK, H. Liu, Y. Ni, F. F. Wu, R. Hui, Tuning the fuzzy damping controller for UPFC through genetic algorithm with comparison to the gradient descent training, Int. J. EPES, vol. 27, 2005, pp. 275-283.
16. A. Kazemi, M. V. Sohrforouzani, Power system damping using fuzzy controlled facts devices, Int. J. EPES, vol. 28, 2006, pp. 349-357.
17. P. K. Dash, S. Morris, S. Mishra, Design of a Nonlinear Variable-Gain Fuzzy Controller for FACTS Devices, IEEE Trans. on Control Systems Technology, vol. 12, 2004, pp. 428-438.
18. P. K. Dash, S. Mishra, G. Panda, A radial basis function neural network controller for UPFC, IEEE Trans. Power Syst., vol. 15, 2000, pp. 1293-1299.
19. S. Mishra, Neural-Network-Based Adaptive UPFC for Improving Transient Stability Performance of Power System, IEEE Trans. Neural Networks, vol. 7, 2006, pp. 461-470.
20. V. K. Chandrakari, A. G., Kothari, Comparison of RBFN based STATCOM, SSSC and UPFC Controllers for Transient Stability improvement, PSCE, 2006, pp. 784-791.
21. P. Kundur, Power system stability and control (Maiderherd McGraw Hill, 1994).
22. R. Storn, Differential Evolution, A Simple and Efficient Heuristic Strategy for Global Optimization over Continuous Spaces, JGO, vol. 11, 1997, pp. 341-359.
23. B.V. Babu, Process plant simulation (Oxford University Press, 2004).
24. L. S. Roger, M. Srinivas, G. P. Rangaiah, Global Optimization of Benchmark And Phase Equilibrium Problems Using Differential Evolution, Journal of the institution of engineers, vol. 46.
25. J. Tvrdík, Competitive differential evolution and genetic algorithm in GA-DS Toolbox, Technical Computing Prague, 2006, pp. 99-99.
26. D. Karagoba, S. A. Okdem, Simple and Global Optimization Algorithm for Engineering Problems: Differential Evolution Algorithm, Turk J Elec Engin, vol. 12, no.1, 2004.
27. A. Vasan, K. Raju, Optimal Reservoir Operation Using Differential Evolution, Available: http://www.icsi.berkeley.edu/~storn/Paper_Roorkee.pdf, 2000.
28. Jones, K. O., Bouffet, A. "Comparison of ant colony optimization and differential evolution", CompSysTech, 285, No. 25, 2007.
29. S. K. Mishra, Global Optimization by Differential Evolution and Particle Swarm Methods: Evaluation on Some Benchmark Functions, Available at SSRN: http://ssrn.com/abstract=933827, 2006.
30. th International Conference on Optimization of Electrical and Electronic Equipment ~ OPTIM 2008~, Brasov, Romania, 2008, pp.185-190.
31. B. Yu, X. He, Training Radial Basis Function Networks with Differential Evolution, Transactions on Engineering, Computing and Technology, 2006.
32. K. M. Faraoun, A. Boukelif, Neural networks learning improvement using the K-means clustering algorithm to detect network intrusions, IJCI, vol. 5, 2006, pp. 28-36.
33. Baghaee, H. R.; Mirsalim, M.; Kashefi-Kaviani, A.; Gharehpetian, G. B., Optimal Allocation of Multi-Type FACTS Devices to Improve Security and Reduce the Losses and Fault Level Using Multi-Objective Particle Swarm Optimization, International Review of Electrical Engineering (IREE), vol. 5, n. 2, 2010, pp. 409-415.
34. Rahimzadeh, S.; Bina, M. Tavakoli, Planning Required for FACTS Devices to Improve the Steady State Efficiency of Restructured Power Systems: A Review, International Review of Electrical Engineering (IREE), vol. 4, n. 3, 2009, pp. 417-424.