Real Coded Biogeography-Based Optimization for Environmental Constrained Dynamic Optimal Power Flow

- Journal title : Journal of Electrical Engineering and Technology
- Volume 10, Issue 1, 2015, pp.56-63
- Publisher : The Korean Institute of Electrical Engineers
- DOI : 10.5370/JEET.2015.10.1.056

Title & Authors

Real Coded Biogeography-Based Optimization for Environmental Constrained Dynamic Optimal Power Flow

Kumar, A. Ramesh; Premalatha, L.;

Kumar, A. Ramesh; Premalatha, L.;

Abstract

The optimization is an important role in wide geographical distribution of electrical power market, finding the optimum solution for the operation and design of power systems has become a necessity with the increasing cost of raw materials, depleting energy resources and the ever growing demand for electrical energy. In this paper, the real coded biogeography based optimization is proposed to minimize the operating cost with optimal setting of equality and inequality constraints of thermal power system. The proposed technique aims to improve the real coded searing ability, unravel the prematurity of solution and enhance the population assortment of the biogeography based optimization algorithm by using adaptive Gaussian mutation. This algorithm is demonstrated on the standard IEEE-30 bus system and the comparative results are made with existing population based methods.

Keywords

Biogeography based optimization;Diversity;Dynamic optimal power flow;Real coded;Searching ability;

Language

English

References

1.

M. Olofsson, G. Andersson and L. Soder, “Linear Programming Based Optimal Power Flow using Second Order Sensitivities,” IEEE Transactions on Power Systems, vol. 10, no. 3, pp. 1691-1697, Aug. 1995.

2.

H. Wei , H. Sasaki, J. Kubokawa and R. Yokoyama, “An Interior Point Nonlinear Programming for Optimal Power Flow Problems with a Novel Structure Data,” IEEE Transactions on Power Systems, vol. 13, no. 3, pp. 870-877, Aug. 1998.

3.

RC Burchett, HH Happ and DR Vierath, “Quadratically Convergent Optimal Power Flow”, IEEE Transactions on Power Apparatus Systems, vol. 103, no. 11, pp. 3267-3275, Nov. 1984.

4.

D. I. Sun, B. Ashley, B. Brewer, A. Hughes and W. F. Tinney, “Optimal Power Flow by Newton Approach,” IEEE Transactions on Power Apparatus and System, vol. 103, no. 6, pp. 2864-2880, Oct. 1984.

5.

X. Yan and V. H Quantana, “Improving an Interior Point Based OPF by Dynamic Adjustments of Step Sizes and Tolerances,” IEEE Transactions on Power Systems, vol. 14, no. 2, pp. 709-717, May 1999.

6.

J. A. Momoh and J. Z. Zhu, “Improved Interior Point Method for OPF Problems,” IEEE Transactions on Power Systems, vol. 14, no. 3, pp. 1114-1120, Aug. 1999.

7.

R. Shoults and D Sun, “Optimal Power Flow Based on P-Q Decomposition” IEEE Transactions on Power Apparatus Systems, vol. 101, no. 2, pp. 397-405, Feb. 1982.

8.

A. L. Costa and A. S. Costa, “Energy and Ancillary Service Dispatch through Dynamic Optimal Power Flow,” Electric Power systems Research, vol. 77, no. 8, pp. 1047-1055, Jun. 1997.

9.

J.S. Dhillon, S.C. Parti and D.P. Kothari, “Stochastic Economic Emission Load Dispatch,” Electric Power System Research, vol. 26, no. 3, pp. 179-186, Apr. 1993.

10.

D. Devaraj and B. Yegnanarayana, “Genetic Algorithm Based Optimal Power Flow for Security Enhancement,” Generation, Transmission and Distribution, IEE Proceedings, vol. 152, no. 6, pp. 899-905, Nov. 2005.

11.

L. L. Lai and J. T Ma, “Improved Genetic Algorithms for Optimal Power Flow under both Normal and Contingent Operation States,” Int J Electrical Power Energy Systems, vol. 19, no. 5, pp. 287-292, Jun. 1997.

12.

A. G. Bakirtzis, P. N. Biskas, C. E. Zoumas and V. Petridis, “Optimal Power Flow by Enhanced Genetic Algorithm,” IEEE Transactions on Power Systems, vol. 17, no. 2, pp. 229-236, May 2002.

13.

Y. R. Sood, “Evolutionary Programming based Optimal Power Flow and its Validation for Deregulated Power System Analysis,” Int J Electrical Power Energy Systems, vol. 29, no. 1, pp. 65-75, Jan. 2007.

14.

M. A. Abido, “Optimal Power Flow using Tabu Search Algorithm,” Electrical Power Component Systems, vol. 30, pp. 469-483, May 2002.

15.

C. A. Roa-Sepulveda and B. J. Pavez-lazo, “A Solution to the Optimal Power Flow using Simulated Annealing,” Int J Electrical Power Energy System, vol. 25, no. 1, pp. 47-57, Jan. 2003.

16.

M. A. Abido, “Optimal Power Flow using Particle Swarm Optimization,” Int J Electrical Power Energy Systems, vol. 24, no. 7, pp. 563-571, Oct. 2002.

17.

A. A. Abou El Ela, M. A. Abido and S. R. Spea, “Optimal Power Flow using Differential Evolution Algorithm,” Electrical Power Systems Research, vol. 80, no. 7, pp. 878-885, July 2010.

18.

S. Sayah and Zehar Kh, “Modified Differential Evolution Algorithm for Optimal Power Flow with Non-smooth Cost Function,” Energy Conversion Management, vol. 49, pp. 3036-3042, Aug. 2008.

19.

T. Niknam, M. R. Narimani, M. Jabbari and A. R. Malekpour, “A Modified Shuffle Frog Leaping Algorithm for Multi-Objective Optimal Power Flow,” Energy, vol. 36, pp. 6420-6432, Oct. 2011.

20.

M. Rezaei Adaryani and A. Karami, “Artificial Bee Colony Algorithm for Solving Multi-objective Optimal Power Flow Problem,” Int J Electrical Power Energy Systems, vol. 53, pp. 219-230, Apr. 2013.

21.

A. Bhattacharya and Chattopadhyay, “Application of Biogeography-Based Optimization to Solve Different Optimal Power Flow Problems,” IET Generation, Transmission & Distribution, vol.5, no.1, pp.70-80, Jan. 2011.

22.

Dan Simon, “Biogeography-Based Optimization,” IEEE Transactions on Evolutionary Computation, vol. 12, no.6, pp.702-713, Dec. 2008.

23.

R. MacArthur and E. Wilson, “The Theory of Biogeography,” Princeton, NJ: Princeton Univ. Press, 1967.

24.

Wenyin Gong, Zhihua Cai, Charles X. Ling and Hui Li, “A Real-Coded Biogeography-Based Optimization with Mutation”, Applied Mathematics and Computation, vol. 216, no. 9, pp. 2749-2758, July 2010.

25.

P. Venkatesh, R. Gnanadass, and Narayana Prasad Padhy, “Comparison and Application of Evolutionary Programming Techniques to Combined Economic Emission Dispatch with Line Flow Constraints,” IEEE Transaction on Power Systems, vol. 18, no. 2, pp. 688-697, May 2003.

26.

R. D. Zimmerman, C. E. Murillo-Sanchez, and R. J. Thomas, “MATPOWER: Steady-State Operations, Planning and Analysis Tools for Power Systems Research and Education,” IEEE Transaction on Power Systems, vol. 26, no. 1, pp. 12-19, Feb. 2011.

27.

P. A. D. Vimal Raj, T. G. Palanivelu, R. Gnanadass, “Optimal Power Flow Solution for Combined Economic Emission Dispatch Problem using Particle Swarm Optimization Technique,” Journal of Electrical Systems, vol. 3, no. 1, pp. 13-25, 2007.