A new hybrid fuzzy adaptive particle swarm optimization for non-convex economic dispatch

International Journal of Innovative Computing, Information and Control

Volumn 7, Issue 1, 2011, Pages 189-202

  Niknam, Taher ^a   Mojarrad, Hasan Doagou ^a   Nayeripour, Majid ^a  

^a SHIRAZ UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Economic dispatch; Fuzzy adaptive particle swarm optimization; Hybrid evolutionary algorithms

Indexed keywords

BEST POSITION; DIFFERENTIAL EVOLUTION; ECONOMIC DISPATCH; EFFECTIVE TOOL; ELECTRIC POWER; FUZZY ADAPTIVE; FUZZY ADAPTIVE PARTICLE SWARM OPTIMIZATION; GLOBAL MINIMA; HYBRID ALGORITHMS; HYBRID EVOLUTIONARY ALGORITHM; INERTIA WEIGHT; LEARNING FACTOR; LOCAL OPTIMA; NON-LINEAR OPTIMIZATION PROBLEMS; OPERATION AND MANAGEMENT; OPTIMIZATION PROCESS; OPTIMIZERS; OPTIMUM SOLUTION; POPULATION DIVERSITY; POWER SYSTEMS; SEARCH CAPABILITIES; THERMAL UNITS; VALVE-POINT LOADINGS;

ALGORITHMS; FUZZY LOGIC; FUZZY SETS; PROBLEM SOLVING; WATER ANALYSIS;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 78650895495     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (35)

1. D. K. He, F. L. Wang and Z. Z. Mao, Hybrid genetic algorithm for economic dispatch with valve-point effect, Electrical Power Systems Research, vol.78, no.4, pp.626-633, 2008.
2. P. Subbaraj, R. Rengaraj and S. Salivahanan, Enhancement of combined heat and power economic dispatch using self adaptive real-coded genetic algorithm, Applied Energy, vol.86, no.6, pp.915-921, 2009.
3. K. Ashwani and G. Wenzhong, Pattern of secure bilateral transactions ensuring power economic dispatch in hybrid electricity markets, Applied Energy, vol.86, no.7-8, pp.1000-1010, 2009.
4. N. Noman and H. Iba, Differential evolution for economic load dispatch problems, Electrical Power-Systems Research, vol.78, no.8, pp.1322-1331, 2008.
5. T. Niknam, H. D. Mojarrad and M. Nayeripour, A new fuzzy adaptive particle swarm optimization for non-smooth economic dispatch, J. Energy, vol.35, no.4, pp. 1764-1778, 2010.
6. A. f. Selvakumar and K. Thanushkodi, Anti-predatory particle swarm optimization: Solution to nonconvex economic dispatch problems, Electrical Power Systems Research, vol.78, no.1, pp.2-10, 2008.
7. L. G. Papageorgiou and E. S. Fraga, A mixed integer quadratic programming formulation for the economic dispatch of generators with prohibited operating zones, Electrical Power Systems Research, vol.77, no.10, pp.1292-1296, 2007.
8. S. K. Wang, J. P. Chiou and C. W. Liu, Non-smooth/nonconvex economic dispatch by a novel hybrid differential evolution algorithm, IET Generation Transmission and Distribution, vol.1, no.5, pp.793-803, 2007.
9. J. Cai, X. Ma, L. Li, Y. Yang, H. Peng and X. Wang, Chaotic ant swarm optimization to economic dispatch, Electrical Power Systems Research, vol.77, no.10, pp.1373-1380, 2007.
10. P. H. Chen and H. C. Chang, Large-scale economic dispatch by genetic algorithm, IEEE Transactions on Power Systems, vol.10, no.4, pp. 1919-1926, 1995.
11. S. Baskar, P. Subbaraj and M. V. C. Rao, Hybrid real coded genetic algorithm solution to economic dispatch problem, Computers and Electrical Engineering, vol.29, no.3, pp.407-419, 2003.
12. V. M. Lin,F. S. Cheng, M. T. Tsay, An improved tabu search for economic dispatch with multiple minima, IEEE Transactions on Power Systems, vol.17, no.1, pp.108-112, 2002.
13. K. P. Wong and Y. W. Wong, Genetic/simulated-annealing approaches to economic dispatch, IEEE Proceedings Generation Transmission and Distribution, vol.141, no.5, pp.507-513, 1994.
14. J. B. Park, K. S. Lee, J. R. Shin and K. Y. Lee, A particle swarm optimization for economic dispatch with non-smooth cost functions, IEEE Transactions on Power Systems, vol.20, no.1, pp.34-42, 2005.
15. Z. L. Gaing, Particle swarm optimization to solving the economic dispatch considering the generator constraints, IEEE Transactions on Power Systems, vol.18, no.3, pp.1187-1195, 2003.
16. X. Yuan, A. Su, Y. Yuan, H. Nie and L. Wang, An improved PSO for dynamic load dispatch of generators with valve-point effects, Energy, vol.34, no.1, pp.67-74, 2009.
17. C. Liu and Y. Wang, A new evolutionary algorithm for multi-objective optimization problems, ICIC Express Letters, vol.1, no.1, pp.93-98, 2007.
18. T. Uno, H. Katagiri and K. Kato, An evolutionary multi-agent based search method for stackel-berg solutions of bilevel facility location problems, International Journal of Innovative Computing, Information and Control, vol.4, no.5, pp.1033-1042, 2008.
19. C. Liu and Y. Wang, A new dynamic multi-objective optimization evolutionary algorithm, International Journal of Innovative Computing, Information and Control, vol.4, no.8, pp.2087-2096, 2008.
20. L. Dos, S. Coelho and V. C. Mariani, Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect, IEEE Transactions on Power Systems, vol.21, no.2, pp.989-996, 2006.
21. T. A. A. Victoire and A. E. Jeyakumar, Hybrid PSO-SQP for economic dispatch with valve-point effect, Electrical Power Systems Research, vol.71, no.1, pp.51-59, 2004.
22. S. C. Neoh, A. Marzuki, N. Morad, C. P. Lira and Z. A. Aziz, An interactive evolutionary algorithm for MMIC low noise amplifier design, ICIC Express Letters, vol.3, no.1, pp.15-20, 2009.
23. J. Kennedy and R. Eberhart, Particle swarm optimization, IEEE International Conf. on Neural Networks, vol.4, pp. 1942-1948, 1995.
24. T. Niknam, M. Nayeripour, J. Olamaei and A. Arefi, An efficient hybrid evolutionary optimization algorithm for daily volt/var control at distribution system including DGs, Int. Rev. Electr. Eng., vol.3, no.3, pp.1-11, 2008.
25. J. Olamaei, T. Niknam and G. Gharehpetian, Application of particle swarm optimization for distribution feeder reconfiguration considering distributed generators, Applied Mathematics and Computation, vol.200, no. 1-2, pp.575-586, 2008.
26. R. Storn and K. Price, Differential evolution -A simple and efficient heuristic for global optimization over continuous spaces, Journal of Global Optimization, vol.11, no.4, pp.341-359, 1997.
27. P. Bajpai and S. N. Singh, Fuzzy adaptive particle swarm optimization for bidding strategy in uniform price spot market, IEEE Transactions on Power Systems, vol.22, no.4, pp.2152-2160, 2007.
28. T. Niknam, A new fuzzy adaptive hybrid particle swarm optimization algorithm for non-linear, non-smooth and non-convex economic dispatch problem, Applied Energy, vol.87, no.1, pp.327-339, 2010.
29. C. Lai, C. H. Wu and M. Tsai, Feature selection using particle swarm optimization with application in spam filtering, International Journal of Innovative Computing, Information and Control, vol.5, no.2, pp.423-432, 2009.
30. N. Sinha, R. Chakrabarti and P. K. Chattopadhyay, Evolutionary programming techniques for economic load dispatch, IEEE Transactions Evolutionary Computation, vol.7, no.1, pp.83-94, 2003.
31. D. C. Walters and G. B. Sheble, Genetic algorithm solution of economic dispatch with valve point loading, IEEE Transactions on Power Systems, vol.8, no.3, pp.1325-1332, 1993.
32. K. S. Swarup and P. R. Kumar, A new evolutionary computation technique for economic dispatch with security constraints, Electrical Power Energy Systems, vol.28, no.4, pp.273-283, 2006.
33. A. P. Neto, C. Unsihuay and O. R. Saavedra, Efficient evolutionary strategy optimisation procedure to solve the nonconvex economic dispatch problem with generator constraints, IEEE Proceedings Generation Transmission and Distribution, vol.152, no.5, pp.653-660, 2005.
34. T. Niknam, A. Khodaei and F. Fallahi, A new decomposition approach for the thermal unit commitment problem, Applied Energy, vol.86, no.9, pp. 1667-1674, 2009.
35. A. I. Selvakumar and T. Khanushkodi, A new particle swarm optimization solution to non-convex economic dispatch problems, IEEE Transactions on Power Systems, vol.22, no.1, pp.42-51, 2007.