Minimizing Power Loss Using Modified Artificial Bee Colony Algorithm


  • Nur Azlin Ashiqin Mohd Amin Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perlis Branch, Arau Campus
  • Siti Hafawati Jamaluddin Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perlis Branch, Arau Campus
  • Nur Syuhada Muhammat Pazil Faculty of Computer & Mathematical Sciences,Universiti Teknologi MARA, Kampus Jasin, Melaka
  • Norwaziah Mahmud Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perlis Branch, Arau Campus
  • Norhanisa Kimpol Universiti Malaysia Perlis



Modified Artificial Bee Colony (MABC) algorithm, electrical energy, power loss, power system.


Electrical energy losses are found in any part of the power system. In the power system, it is essential to minimize the real power loss in transmission lines. The voltage deviation at the load buses through controlling the reactive power flow is very important. This ensures the secured operation of power systems regarding voltage stability and the economics of the process due to loss minimization. In this paper, the Modified Artificial Bee Colony (MABC) algorithm is implemented to solve the power system's optimal reactive power flow problem. Generator bus voltages, transformer tap positions, and settings of switched shunt of compensators are used as decision variables to control the reactive power flow. These control variable values are adjusted for loss reduction. MABC algorithm is tested on the standard IEEE-30 bus test system. The results are compared with Firefly algorithm (FA) and Artificial Bee Colony (ABC) algorithm method to prove the effectiveness of the newest algorithm. The power loss results are quite productive, and the algorithm is the most efficient than the other methods such as ABC algorithm and FA algorithm. These results are produced by Matlab 2017b.


Download data is not yet available.


Akay, B., & Karaboga, D. (2012). A modified artificial bee colony algorithm for real-parameter optimization. Information Sciences, 192, 120-142.

Anumaka, M. C. (2012). Analysis oftechnical losses in electrical power system (Nigerian 330KV network as a case study). Technical Losses in Electrical Power System, 12(2), 320-327.

Baskar, S., & Pooja, S. (2017). Minimization of real power loss using genetic algorithm. Journal of Invention in Computer Science and Communication Technology (JICSCT), 3(6), 1-10.

Deenadhayalan, M. H. (2014). Real power loss minimization using firefly algorithm. IJAICT, 1(8), 667-682.

Dixit, S., Srivastava, L., & Agnihotri, G. (2014). Minimization of power loss and voltage deviation by SVC placement using GA. International Journal of Control and Automation, 7(6), 95-108.

Monti, A., & Ponci, A. (2015). Electric power system. Springer-Verlag Berlin Heidelberg, 12, 31-65.

PSCAD. (2018). IEEE 30 Bus System.

Rao, R. S., Narasimham, S. V. L., Ramalingaraju, M. (2008). Optimization of distribution network configuration for loss reduction using artificial bee colony algorithm. International Scholarly and Scientific & Innovation, 2(9), 1964-1970.

Sankaramoorthy, M., & Veluchamy, M. (2017). A hybric MACO and BFOA algorithm for power loss minimization and total cost reduction in distribution systems. Turkish Joutnal of Elecrtrical Engineering & Computer Sciences, 25, 337-351.

Singh, S., Jain, V. K., & Prasad, U. (2017). Power loss reduction in power system based on PSO: case study. International Journal of Computer Application, 164(10), 22-26.

Sulaiman, N., Mohammad-Salleh, J., & Abro, A. G. (2013). A modified artificial bee colony (ja-abc) optimization algorithm. International Conference on Applied Mathematics and Computational Method in Engineering, 74-79.




How to Cite

Nur Azlin Ashiqin Mohd Amin, Jamaluddin, S. H., Nur Syuhada Muhammat Pazil, Norwaziah Mahmud, & Norhanisa Kimpol. (2021). Minimizing Power Loss Using Modified Artificial Bee Colony Algorithm. Journal of Computing Research and Innovation, 6(2), 111–118.



General Computing

Most read articles by the same author(s)