A fuzzy multi-objective multi-case genetic-based optimization for allocation of FACTS devices to improve system static security, power loss and transmission line voltage profiles

International Review of Electrical Engineering

Volumn 5, Issue 4, 2010, Pages 1616-1626

  Deihimi, A ^a   Javaheri, H ^a  

^a BU ALI SINA UNIVERSITY   (Iran)

Author keywords

Fuzzy decision making; Genetic algorithm; Optimal allocation of FACTS devices; Static power system security; Transmission line voltage profile

Indexed keywords

EID: 79956122065     PISSN: 18276660     EISSN: 25332244     Source Type: Journal    
DOI: None     Document Type: Article

References (17)

1. N.G. Hingorani, L. Gyugyi, Understanding FACTS: concepts and technology of flexible AC transmission systems (IEEE, Inc., 2000).
2. S.N. Singh, Location of FACTS devices for enhancing power systems' security, Conference on Large Engineering Systems Power Engineering ~LESCOPE '01~, July 11-13, 2001, Halifax, NS, Canada.
3. S.H. Song, J.U. Lim, S.I. Moon, Installation and operation of FACTS devices for enhancing steady-state security, Electric Power System Research, vol. 70 n. 2, 2004, pp. 7-15.
4. S.N. Singh, A.K. David, Optimal location of FACTS devices for congestion management, Electric Power System Research, vol. 58 n. 2, June 2001, pp. 71-79.
5. T. Jain, S.N. Singh, S.C. Srivastava, Dynamic ATC enhancement through optimal placement of FACTS controllers, Electric Power System Research, vol. 79 n. 11, November 2009, pp. 1473-1482.
6. P. Paterni, S. Vitet, M. Bena, A. Yokoyama, Optimal location of Phase shifters in the French Network by genetic algorithm, IEEE Transactions on Power systems, vol. 14 n. 1, February 1999, pp. 37-42.
7. D. Radu, Y. Bésanger, A multi-objective genetic algorithm approach to optimal allocation of multi-type FACTS devices for power systems security, IEEE Power Engineering Society General Meeting, July 13-17, 2003, Toronto, Canada.
8. S. Gerbex, R. Cherkaoui, A.J. Germond, Optimal location of multi-type FACTS devices in a power system by means of genetic algorithm, IEEE Transaction on Power Systems, vol.16 n.3, 2001, pp. 537-544.
9. M. Saravanan, S.M.R. Slochanal, P. Venkatesh, J.P.S. Abraham, Application of particle swarm optimization technique for optimal location of FACTS devices considering cost of installation and system loadability, Electric Power System Research, vol.77 n.3, March 2007, pp. 276-283.
10. Z. Lu, M.S. Li, L. Jiang, Q.H. Wu, Optimal allocation of FACTS devices with multiple objectives achieved by Bacterial Swarming Algorithm, IEEE Power and Energy Society General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, July 20-24, 2008, Pittsburgh, Pennsylvania, USA.
11. N. Yorino, E.E. El-Araby, H. Sasaki, S. Harada, A new formulation for FACTS allocation for security enhancement against voltage collapse, IEEE Transactions on Power Systems, vol. 18 n. 1, 2003, pp. 3-10.
12. H. R. Baghaee, M. Mirsalim, A. Kashefi-Kaviani, G. B. Gharehpetian, Optimal allocation of multi-type FACTS devices to improve security and reduce the losses and fault level using multiobjective particle swarm optimization, International Review of Electrical Engineering (IREE), vol. 4 n. 6 (Part B), December 2009, pp. 1326-1335.
13. A. Laïfa, M. Boudour, Multi-objective particle swarm optimization for FACTS allocation to enhance voltage security, International Review of Electrical Engineering (IREE), vol. 4 n. 5 (Part B), October 2009, pp. 994-1004.
14. M. Joorabian, M. Ebadi, Locating static VAR compensator (SVC) based on small signal stability of power system, International Review of Electrical Engineering (IREE), vol. 4 n. 4, August 2009, pp. 635-641.
15. T.S. Chung, Y.Z. Li, A hybrid GA Approach for OPF with Consideration of FACTS Devices, IEEE Power Engineering Review, vol.21 n.2, February 2001, pp 47-57.
16. J. Baskaran, V. Palanisamy, Optimal location of FACTS devices in a power system solved by a hybrid approach, Nonlinear Analysis, vol. 65 n. 11, December 2006, pp. 2094-2102.
17. C.A.C. Coello, G.B. Lamont, D.A. Van Veldhuizen, Evolutionary Algorithms for Solving Multi-Objective Problems (Springer, 2007).