A hybrid bacterial foraging and differential evolution algorithm for congestion management

European Transactions on Electrical Power

Volumn 20, Issue 7, 2010, Pages 862-871

  Ravikumar Pandi, V ^b   Biswas, Arijit ^a   Dasgupta, Sambarta ^a   Panigrahi, B K ^b  

^a JADAVPUR UNIVERSITY   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

Author keywords

Bacterial foraging; Congestion management; Differential evolution; Optimal power flow; Wheeling transactions

Indexed keywords

BACTERIAL FORAGING; CONGESTION MANAGEMENT; DIFFERENTIAL EVOLUTION; OPTIMAL POWER FLOWS; WHEELING TRANSACTIONS;

GENETIC ALGORITHMS; TRAFFIC CONGESTION;

PROBLEM SOLVING;

EID: 84864670598     PISSN: 1430144X     EISSN: 15463109     Source Type: Journal    
DOI: 10.1002/etep.368     Document Type: Article

References (32)

1. Kumara A, Srivastava SC, Singh SN. Congestion management in competitive power market: a bibliographical survey. Electric Power Systems Research 2005;76:153-164. (Pubitemid 41165547)
2. Alomoush MI, Shahidehpour SM. Contingency-constrained congestion management with a minimum number of adjustments in preferred schedules. Electrical Power and Energy Systems 2000;22:277-290. (Pubitemid 30564132)
3. Rodrigues AB, Da Silva MG. Impact of multilateral congestion management on the reliability of power transactions. Electrical Power and Energy Systems 2003;25:113-122. (Pubitemid 35214167)
4. Purchala K, Meeus L, Belmans R. Implementation aspects of coordinated auctioning for congestion management. IEEE Bologna Power Tech Conference, 23-26 June 2003, Bologna, Italy.
5. Fang RS, David AK. Transmission congestion management in an electricity market. IEEE Transactions on Power Systems 1999;14(3):877-883.
6. Tuan LA, Bhattacharya K, Daalder J. Transmission congestion management in bilateral markets: an interruptible load auction solution. Electric Power Systems Research 2005;74:379-389. (Pubitemid 40612276)
7. Yang H, Zhou R, Zhang Y. A study of the curtailment model for bilateral transaction in power market environment. IEEE PES on PSCE, 29 October-1 November 2006;1663-1667.
8. Ivan Skokljev, Viktor Maksimovic. Congestion management utilizing concentric relaxation. Serbian Journal of Electrical Engineering 2007;4(2):189-206.
9. Sood YR. Evolutionary programming based optimal power flow and its validation for deregulated power system analysis. Electrical power and energy systems 2007;29(1):65-75. (Pubitemid 44634703)
10. Gnanadas R, Padhy NP, Palanivelu TG. A new method for the transmission congestion management in the restructured power market. Journal of Electrical Engineering, Electrika 2007;9(1):52-58.
11. Yesuratnam G, Thukaram D. Congestion management in open access based on relative electrical distances using voltage stability criteria. Electric Power Systems Research 2007;77:1608-1618. (Pubitemid 47348215)
12. Hazra J, Sinha AK. Congestion management using multiobjective particle swarm optimization. IEEE Transactions on Power Systems 2007;22(4):1726-1734. (Pubitemid 350141972)
13. Niimura T, Nakashima T. Multiobjective tradeoff analysis of deregulated electricity transactions. Electrical Power and Energy Systems 2003;25:179-185. (Pubitemid 35411881)
14. Passino KM. Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Systems Magazine 2002;22:52-67. (Pubitemid 34711477)
15. Liu Y, Passino KM. Biomimicry of social foraging bacteria for distributed optimization models, principles, and emergent behaviors. Journal of Optimization Theory and Applications 2002;115(3):603-628. (Pubitemid 39583280)
16. Gazi V, Passino KM. Stability analysis of swarms in an environment with an attractant/repellent profile. Proceedings of American Control Conference, Anchorage, Alaska, May 2002;1819-1824.
17. Gazi V, Passino KM. Stability analysis of swarms. Proceedings of American Control Conference, Anchorage, Alaska, May 2002;1813-1818.
18. Storn R, Price K. Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization 1997;11(4):341-359. (Pubitemid 127502202)
19. Price K, Storn R, Lampinen J. Differential Evolution-A Practical Approach to Global Optimization. Springer: New York, 2005. ISBN: 3-540-20950-6.
20. Arijit Biswas, Sambarta Dasgupta, Swagatam Das, Ajith Abraham. A synergy of differential evolution and bacterial foraging algorithm for global optimization. International Journal on Neural and Mass-Parallel Computing and Information Systems, Neural Network World, 2007;17(6):607-626. (Pubitemid 351237999)
21. Holland JH. Adaptation in Natural and Artificial Systems. University of Michigan Press: Ann Arbor, 1975.
22. Goldberg DE, Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley: Reading, MA, 1989.
23. Bakirtzis AG, Biskas PN, Zoumas CE, Petridis V. Optimal power flow by enhanced genetic algorithm. IEEE Transactions on Power Systems 2002;17(2):229-236. (Pubitemid 34741681)
24. http://www.icsi.berkeley.edu/~storn/code.html
25. www.mathworks.com
26. Vesterstrøm J, Thomson R. A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems. Proceedings of Sixth Congress on Evolutionary Computation (CEC-2004), IEEE Press.
27. Lampinen J, Zelinka I. On stagnation of the differential evolution algorithm. Proceedings of MENDEL 2000, 6th International Mendel Conference on Soft Computing, Ošmera, Pavel (ed.), Brno, Czech Republic 7-9 June 2000.
28. Biswas A, Dasgupta S, Das S, Abraham A. Synergy of PSO and bacterial foraging optimization: a comparative study on numerical benchmarks. Second International Symposium on Hybrid Artificial Intelligent Systems (HAIS 2007), Advances in Soft computing Series, Springer Verlag, Germany, Corchado, Innovations in Hybrid Intelligent Systems, ASC 44, 2007;255-263.
29. Noman N, Iba H. Enhancing differential evolution performance with local search for high dimensional function optimisation. Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, June 2005;967-974. (Pubitemid 43226403)
30. Das S, Konar A, Chakraborty UK. An improved particle swarm optimization algorithm for faster global search. ACM-SIGEVO Proceedings of Genetic and Evolutionary Computation Conference (GECCO-2005), Washington DC, June 2005.
31. Kim DH, Abraham A, Cho JH. A hybrid genetic algorithm and bacterial foraging approach for global optimization. Information Sciences 2007;177(18):3918-3937. (Pubitemid 46961984)
32. http://www.pserc.cornell.edu/matpower