Solution of optimal power flow using nondominated sorting multi objective gravitational search algorithm

International Journal of Electrical Power and Energy Systems

Volumn 62, Issue , 2014, Pages 323-334

  Bhowmik, Arup Ratan ^a   Chakraborty, A K ^a  

^a NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Active power loss minimization; Bus voltage deviation minimization; Multi objective nondominated sorting gravitational search algorithm; Optimal power flow; Total fuel cost minimization; Voltage stability enhancement

Indexed keywords

ACOUSTIC GENERATORS; COMPUTER SIMULATION; ELECTRIC LOAD FLOW; NUMERICAL METHODS; PARETO PRINCIPLE; VOLTAGE STABILIZING CIRCUITS;

ACTIVE POWER LOSS MINIMIZATIONS; BUS VOLTAGE; FUEL COST MINIMIZATIONS; NON-DOMINATED SORTING; OPTIMAL POWER FLOWS; STABILITY ENHANCEMENT;

LEARNING ALGORITHMS;

EID: 84901605428     PISSN: 01420615     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijepes.2014.04.053     Document Type: Article

References (34)

1. A.A. Abou El-Ela, and M.A. Abido Optimal operation strategy for reactive power control modeling Simulat Contr Part A 41 3 1992 19 40 AMSE Press
2. R. Mota-Palomino, and V.H. Quintana Sparse reactive power scheduling by a penalty-function linear programming technique IEEE Trans Power Syst 1 3 1986 31 39 (Pubitemid 16629601)
3. H. Dommel, and W. Tinny Optimal power flow solution IEEE Trans Power Appart Syst 87 10 1968 1866 1876
4. R.C. Burchett, H.H. Happ, and D.R. Vierath Quadratically convergent optimal power flow IEEE Trans Power Apparat Syst 103 11 1984 3267 3276
5. D.I. Sun, B. Ashley, B. Brewer, A. Hughes, and W.F. Tinney Optimal power flow by Newton approach IEEE Trans Power Appart Syst 103 10 1984 2864 2875
6. A. Santos Jr, and C.G.R.M. Da Optimal power flow solution by Newton's method applied to an augmented Lagrangian function IEE Proc Gen Trans Distr 142 1 1995 33 36
7. X. Yan, and V.H. Quintana Improving an interior point based OPF by dynamic adjustments of step sizes and tolerances IEEE Trans Power Syst 14 2 1999 709 717
8. L.L. Lai, and J.T. Ma Improved genetic algorithms for optimal power flow under both normal and contingent operation states Int J Electr Power Energy Syst 19 5 1997 287 292 (Pubitemid 127412160)
9. A.G. Bakirtzis, P.N. Biskas, C.E. Zoumas, and V. Petridis Optimal power flow by enhanced genetic algorithm IEEE Trans Power Syst 17 2 2002 229 236 (Pubitemid 34741681)
10. K.M. Sailaja, and S. Maheswarapu Enhanced genetic algorithm based computation technique for multi-objective optimal power flow Int J Electr Power Energy Syst 32 6 2010 736 742
11. W. Ongsakul, and T. Tantimaporn Optimal powers flow by improved evolutionary programming Electr Power Comp Syst 34 1 2006 79 95 (Pubitemid 43148738)
12. J. Yuryevich, and K.P. Wong Evolutionary programming based optimal power flow algorithm IEEE Trans Power Syst 14 4 1999 1245 1250 (Pubitemid 32082778)
13. M.A. Abido Optimal power flow using particle swarm optimization Int J Electr Power Energy Syst 24 7 2002 563 571 (Pubitemid 34532350)
14. Zaro FR, Abido MA. Multi-objective particle swarm optimization for optimal power flow in a deregulated environment of power systems. In: 11th International conference on intelligent systems design and applications; 2011. p. 1122-7.
15. E.E.A.A. Abou, and M.A. Abido Optimal power flow using differential evolution algorithm Electr Power Syst Res 80 7 2010 878 885
16. M. Varadarajan, and K.S. Swarup Solving multi-objective optimal power flow using differential evolution IET Gen Trans Dist 2 5 2008 720 730
17. Abido MA, Al-Ali NA. Multi-objective differential evolution for optimal power flow. In: Int. conf. on power engineering, energy and electrical drives (POWERENG); 2009. p. 101-6.
18. S. Sayah, and K. Zehar Modified differential evolution algorithm for optimal power flow with non-smooth cost functions Energy Convers Manage 49 11 2008 3036 3042
19. T. Niknam, R.M. Narimani, M. Jabbari, and R.A. Malekpour A modified shuffle frog leaping algorithm for multi-objective optimal power flow Energy 36 11 2011 6420 6432
20. A. Khorsandi, A. Alimardani, B. Vahidi, and S.H. Hosseinian Hybrid shuffled frog leaping algorithm and Nelder-Mead simplex search for optimal reactive power dispatch IEE Proc Gen Trans Distr 5 2011 249 256
21. S. Sivasubramani, and K.S. Swarup Multi-objective harmony search algorithm for optimal power flow problem Int J Electr Power Energy Syst 33 3 2011 745 752
22. M.R. Adaryani, and A. Karami Artificial bee colony algorithm for solving multi-objective optimal power flow problem Int J Electr Power Energy Syst 53 2013 219 230
23. A. Khorsandi, S.H. Hosseinian, and A. Ghazanfari Modified artificial bee colony algorithm based on fuzzy multi-objective technique for optimal power flow problem Electr Power Syst Res 95 2013 206 213
24. A. Bhattacharya, and P.K. Chattopadhyay Application of biogeography-based optimisation to solve different optimal power flow problems IET Gen Trans Distr 5 1 2011 70 80
25. S. Duman, U. Guvenc, Y. Sonmez, and N. Yorukeren Optimal power flow using gravitational search algorithm Energy Convers Manage 59 2012 86 95
26. Hassanzadeh HR, Rohani M. A Multi-objective gravitational search algorithm. In: Second international conference on computational intelligence communication systems and networks (CICSyN); 2010. p. 7-12.
27. E. Rashedi, H. Nezamabadi-pour, and S. Saryazdi GSA: a gravitational search algorithm Inf Sci 179 3 2009 2232 2248
28. Rao SB, Vaisakh K. Application of ACSA for solving multi-objective optimal power flow problem with load uncertainty. In: IEEE international conference on emerging trends in computing, communication and nanotechnology; 2013. p. 764-71.
29. L. Cagnina, S. Esquivel, and C.A. Coello A particle swarm optimizer for multi-objective optimization J Comput Sci Technol 5 4 2005 204 210
30. E. Zitzler, L. Thiele, M. Laumanns, C.M. Fonseca, and V.G.D. Fonseca Performance assessment of multiobjective optimizers: an analysis and review IEEE Trans Evol Comput 7 2 2003 117 132
31. M. Reyes-Sierra, and C.A.C. Coello Multi-objective particle swarm optimizers: a survey of the state-of-the-art Int J Comput Intell Res 2 3 2006 287 308
32. N. Hadi, N. Mahdi, and S. Patrick A multi objective gravitational search algorithm based on non-dominated sorting Int J Swarm Intell Res 3 3 2012 32 49
33. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan A fast and elitist multiobjective genetic algorithm: NSGA-II IEEE Trans Evol Comput 6 2 2002 182 197 (Pubitemid 34555372)
34. Power System Test Case Archieve. < http://www.ee.washington.edu/ research/pstca/pf30/pg-tca30bus.html >; 2006.