Multi-objective particle swarm optimization for FACTS allocation to enhance voltage security

International Review of Electrical Engineering

Volumn 4, Issue 5, 2009, Pages 994-1004

  Laifa A ^a   Boudour, M ^b  

^a UNIVERSITY OF SKIKDA   (Algeria)

^b UNIVERSITY OF SCIENCES AND TECHNOLOGY HOUARI BOUMEDIENE   (Algeria)

Author keywords

Facts location; Mopso; Svc; Tcsc; Voltage security; Voltage stability

Indexed keywords

EID: 77952244828     PISSN: 18276660     EISSN: 25332244     Source Type: Journal    
DOI: None     Document Type: Article

References (31)

1. C. A. Canizares, Applications of Optimization to Voltage Collapse Analysis, IEEE/PES Summer Meeting, San Diego, July 14, 1998.
2. P. Kundur, J. Paserba, V. Ajjarapu, G. Andersson, A. Bose, C. A. Canizares, N. Hatziargyriou, D. Hill, A. Stankovic, C. Taylor, T. Van Cutsem, V. Vittal, Definition and Classification of Power System Stability, IEEE Trans. on Power Systems, Vol. 19, No. 2, May 2004, pp. 1387-1401.
3. Z. T. Faur, Effects of FACTS Devices on Static Voltage Collapse Phenomena, M.S. dissertation, Dept. Elect. Eng., Univ. of Waterloo, 1996.
4. N. Yorino, E. E. El-Araby, H. Sasaki, S. Harada, A New Formulation for FACTS Allocation for Security Enhancement Against Voltage Collapse, IEEE Trans. on Power Systems, Vol. 18, No. 1, Feb. 2003, pp. 3-10.
5. Bozicek, B. Blazic, I. Papic, Operation of Static Compensator with Time-optimal Current Controller, International Review of Electrical Engineering (IREE), Vol. 3, n. 5, October 2008, pp. 779-787.
6. J. Zhang, J. Y. Wen, S. J. Cheng, J. Ma, A Novel SVC Allocation Method for Power System Voltage Stability Enhancement by Normal Forms of Diffeomorphism, IEEE Trans. on Power Systems, Vol. 22, No. 4, Nov. 2007, pp. 1819-1825.
7. S. Rahimzadeh, M. T. Bina, 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, June 2009, pp. 417-424.
8. G. Hug-Glanzmann, G. Andersson, Coordinated Control of FACTS Devices in Power Systems for Security Enhancement, Bulk Power System Dynamics and Control - VII, August 19-24, 2007, Charleston, South Carolina, USA.
9. S. Mollazei and al., Multi-objective Optimization of Power System Performance with TCSC Using the MOPSO Algorithm, IEEE Trans. on Power Systems, Nov. 2007.
10. R. Mínguez, F. Milano, R. Zárate-Miñano, A. J. Conejo, Optimal Network Placement of SVC Devices, IEEE Trans. On Power Systems, Vol.22, No.4, Nov. 2007.
11. Y. Mansour et al., SVC Placement Using Critical Modes of Voltage Instability, IEEE Trans. on Power Systems, Vol. 9, No. 2, May 1994, pp. 757-763.
12. L. A. S. Pilotto, Determination of Needed Facts Controllers That Increase Asset Utilization of Power Systems, IEEE Trans. on Power Delivery, Vol. 12, No. 1, Jan. 1997, pp. 364-371.
13. M. K. Verma, Optimal Placement of SVC for Static and Dynamic Voltage Security Enhancement, International Journal of Emerging Electric Power Systems, Vol. 2, Issue 2, Article 1050, 2005.
14. A.K. Sharma, Optimal Number and Location of TCSC and Loadability Enhancement in Deregulated Electricity Markets Using MINLP, International Journal of Emerging Electric Power Systems, Vol. 5, Issue 1, Article 6, 2006.
15. Malihe M. Farsangi, H. Nezamabadi-Pour, K. Y. Lee, Multiobjective VAR Planning with SVC for a Large Power System Using PSO and GA, 2006 Power System Conference & Exposition, pp. 274-279.
16. M. A. Abido, Multi-objective Evolutionary Algorithms for Electric Power Dispatch Problem, IEEE Trans. On Evolutionary Computation, Vol. 10, No. 3, June 2006, pp. 315-329.
17. Sode-Yome, N. Mithulananthan, Static Voltage stability Margin Enhancement using STATCOM, TCSC and SSSC, IEEE/PES Transmission and Distribution Conference & Exhibition: Asia and Pacific Dalian, China, 2005.
18. E. Nasr Azadani, S. H. Hosseinian, P. Hasanpor, Optimal placement of multiple STATCOM for voltage stability margin enhancement using particle swarm optimization, Springer-Verlag, Electr Eng, 2008, pp. 503-510.
19. M. J. Reddy, D. N. Kumar, Multi-objective particle swarm optimization for generating optimal trade-offs in reservoir operation, Wiley InterScience, Hydrol. Process. 21, 2007, pp. 2897-2909.
20. E. Zitzler, L. Thiele, Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach, IEEE Transaction on Evolutionary Computation 3, 1999, pp. 257-271.
21. J.D. Knowles, D.W. Corne, Approximating the nondominated front using the Pareto archived evolution strategy, Evolutionary Computation 8, 2000, pp. 149-172,
22. K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast and elitist multi-objective genetic algorithm: NSGA-II, IEEE Transaction on Evolutionary Computation 6, 2002, pp. 182-197.
23. R. Eberhart, J. Kennedy, Particle Swarm Optimization, Proc. of IEEE International Conf. on Neural Networks, Vol. 4, 1995, pp. 1942-1948.
24. J. Park, K. Lee, J. Shin, K. Y. Lee, A Particle Swarm Optimization for Economic Dispatch with Nonsmooth Cost Function, IEEE Trans. on Power Systems, Vol. 20, No.1, Feb. 2005, pp. 34-42.
25. H Yoshida, Y. Fukuyama, A Particle Swarm Optimization for Reactive Power and Voltage Control Considering Voltage Security Assessment, IEEE Trans. On Power Systems, Vol. 15, No. 4, Nov. 2001, pp. 1232-1239.
26. X. Hu, R. Eberhart, Multi-objective optimization using dynamic neighborhood particle swarm optimization, Congress on Evolutionary Computation, IEEE Service Center, Piscataway, New Jersey, 2002, pp. 1677-1681.
27. T. Ray, K. Liew, A swarm metaphor for multi-objective design optimization, Engineering Optimization, Vol. 34, 2002, pp. 141-153.
28. X. Li, A non-dominated sorting particle swarm optimizer for multi-objective optimization, Proc. of Genetic and Evolutionary Computation, In Springer-Verlag Lecture Notes in Computer Science, 2003, pp. 37-48.
29. C.A. Coello Coello, M. S. Lechuga, MOPSO: A proposal for multiple objective particle swarm optimization, Congress on Evolutionary Computation IEEE Service Center, Piscataway, New Jersey, 2002, pp. 1051-1056.
30. J. E. Fieldsend, S. Singh, A multi-objective algorithm based upon particle swarm optimization, an efficient data structure and turbulence, Proc. of the Workshop on Computational Intelligence, Birmingham, UK, 2002, pp. 37-44.
31. S. Mostaghim, J. Teich, Strategies for finding good local guides in multi-objective particle swarm optimization, Proc. IEEE Swarm Intelligence Symposium, IEEE Service Center, Indianapolis, Indiana, 2003, pp. 26-33.