ARTIFICIAL BEE COLONY ALGORITHM TO SOLVE THE OPTIMAL POWER FLOW PROBLEM ON BEN TRE POWER SYSTEM | Tính | TNU Journal of Science and Technology

ARTIFICIAL BEE COLONY ALGORITHM TO SOLVE THE OPTIMAL POWER FLOW PROBLEM ON BEN TRE POWER SYSTEM

About this article

Received: 08/01/24                Revised: 29/02/24                Published: 29/02/24

Authors

1. Tran Huu Tinh Email to author, Can Tho University of Technology
2. Nguyen Tran Long Nhut Dang, Can Tho University of Technology
3. Vo Pha Ga, Can Tho University of Technology
4. Tran Trung Khanh, Can Tho University of Technology
5. Pham Thi Hue, Can Tho University of Technology

Abstract


One of the key requirements in operating the power system is achieving economic efficiency in electricity production, transmission, distribution, and use. To do so, the system must run at the lowest cost possible, which necessitates minimizing both fuel costs and power losses. The optimal power flow (OPF) problem addresses this by seeking to minimize the total generator fuel cost while satisfying all voltage constraints, reactive power limitations at generator nodes, and transformer tap ratios. This research investigates the application of the application of the artificial bee colony (ABC) algorithm for solving the OPF problem. Inspired by the foraging behavior of honeybees, ABC utilizes a population of ‘bees’ to search for optimal solutions and share information with each other. Tests on the Ben Tre power system using PowerWorld software demonstrate the algorithm's ability to find optimal solutions quickly. Therefore, the ABC algorithm shows promise as a viable tool for solving the OPF problem.

Keywords


Power flow; Optimal power flow; Cost of generator fuel; Artificial bee colony algorithm; Power system

References


[1] K. S. Pandya, “A survey of optimal power flow method,” Journal of theoretical and Applied information technology, vol. 4, no. 5, pp. 450-458, 2008.

[2] M. A. Abido, “Optimal power flow using tabu search algorithm,” Electric power components and systems, vol. 30, no. 5, pp. 469-483, 2002.

[3] C. A. Roa-Sepulveda and B. J. Pavez-Lazo, “A solution to the optimal power flow using simulated annealing,” International journal of electrical power & energy systems, vol. 25, no. 1, pp. 47-57, 2003.

[4] M. S. Osman, M. A. Abo-Sinna, and A. A. Mousa, “A solution to the optimal power flow using genetic algorithm,” Applied mathematics and computation, vol. 155, no. 2, pp. 391-405, 2004.

[5] 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, 2002.

[6] A. A. Abou El Ela, M. A. Abido, and S. R. Spea, “Optimal power flow using differential evolution algorithm,” Electric Power Systems Research, vol. 80, no. 7, pp. 878-885, 2010.

[7] B. Allaoua and A. Laoufi, “Optimal power flow solution using ant manners for electrical network,” Advances in Electrical and Computer Engineering, vol. 9, no. 1, pp. 34-40, 2009.

[8] M. A. Abido, “Optimal power flow using particle swarm optimization,” International Journal of Electrical Power & Energy Systems, vol. 24, no. 7, pp. 563-571, 2002.

[9] D. Karaboga, “An idea based on honey bee swarm for numerical optimization,” Technical report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, 2005.

[10] D. L. Le, N. D. Vo, and P. Vasant, “Artificial bee colony algorithm for solving optimal power flow problem,” The Scientific World Journal, vol. 2013, pp. 1–9, 2013, doi:10.1155/2013/159040.

[11] Vietnamese Ministry of Industry and Trade, Decision no. 82/QĐ-BCT on “Ben Tre province's electricity development planning for the period of 2016 - 2025, taking into account 2035,” (in Vietnamese), 2017.

[12] R. D. Zimmerman, C. E. Murillo-Sánchez, and D. Gan, “Matpower user’s manual, version 7.1," Power Systems Engineering Research Center (PSerc): Madison, WI, USA, 2020. [Online]. Available: https://matpower.org/ [Accessed Mar. 31, 2023].




DOI: https://doi.org/10.34238/tnu-jst.9569

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