A Solution to Multi Objective Optimal Power Flow Using Hybrid Cultural-Based Differential Evolution

Article Preview

Abstract:

This paper presents a hybrid Cultural-based Differential Evolution for solving a multi-objective Optimal Power Flow (OPF) in support of power system operation and control . The multi-objective OPF was formulated for tackling with total generation cost and environmental impacts simultaneously. The proposed method was applied to the standard IEEE 30-bus test system. The results show that solving the multi-objective OPF problem by the Cultural-based Differential Evolution is more effective than other swarm intelligence methods in the literature.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1236-1240

Citation:

Online since:

October 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] A. D. Wood, B. F. Wollenberg, Power System Generation and Control, John Wiley & Sons, Inc, (1996).

Google Scholar

[2] Deb K, Multi-objective Optimization using Evolutionary Algorithms, Stanford University Stanford, CA , pp.63-73, (2000).

Google Scholar

[3] D. T. Pham, A. Ghanbarzadeh, E. Koc, S. Otri, S. Rahim and M. Zaidi, Multi-objective Environmental/Economic Using the Bees Algorithm with Weighted Sum, in Proc. of the EU-Korea Conference on Science and Technology, pp.267-274, (2008).

DOI: 10.1007/978-3-540-85190-5_28

Google Scholar

[4] A. Yadav, Multi Objective Optimal Power Flow, Thapar University, Patiala, (2010).

Google Scholar

[5] R.G. Reynolds, An introduction to cultural algorithms, Proceedings of 3rd Annual Conference on Evolutionary Programming, World Scientific, River Edge, NJ, USA, p.131–139, (1994).

Google Scholar

[6] Ricardo Landa Becerra, Carlos A. Coello Coello, A Cultural Algorithm with Differential Evolution to solve constrained optimization problems, Lecture Notes in Computer Science, Volume 3315, pp.881-890, (2004).

DOI: 10.1007/978-3-540-30498-2_88

Google Scholar