Losses Optimization of Induction Motor using Particle Swam Optimization Technique

  • Abel Airoboman Nigeria Defence Academy
  • Habiba Ahmed
  • S. O. Ibrahim Transmission Company of Nigeria, Kaduna, Nigeria
  • H. A. Salihu National Agency for Science and Engineering Infrastructure, Abuja
  • C. Gatta Kaduna Polytechnic
  • D. Chime Nigerian Defence Academy, Kaduna
Keywords: Induction motor, Losses, Motor performance, Optimization techniques, Particle swarm optimization

Abstract

This work is aimed at using Particle Swam Optimization to minimize the losses in an induction motor in order to improve the efficiency. The optimal design of an induction motor for minimum copper loss is taken to minimise the loss of the motor. This was carried out using the power loss equation as the objective function and coding in m-file which is simulated alongside the PSO program in Matlab in order to achieve the best values of the parameter choosen and thereby having a minimized loss. The result of the simulation shows an improvement in the machine's efficiency from to 4.23%. Hence indicating that with the modifications of the choosen parameters, the efficiency of the induction motor can be improved. However, although the PSO is a faster convergence optimization technique, other techniques can be used to make a comparison of the efficiency value.

Downloads

Download data is not yet available.

References

Abdelhadi, B., Benoudijit, A., & Nait, N. (2004). Identification of induction machine parameters using a new adaptive genetic algorithm. Electric Power Components and Systems, 32, 763-784.

Abido, M. A. (2002). Optimal power flow using particle swarm optimization. International Journal Electrical Power and Energy Systems, 24(7): 563-571.

Agbachi, E., Ambafi, J., Tola, O., & Ohize, H. (2012). Design and analysis of three phase induction motor using computer program. World Journal of Engineering and Pure and Applied Science, 2(4):118.

Alam, M. N., (2016). Codes in matlab for particle swarm optimization. Research Gate Indian, Institute of Technology Roorkee.

Allaoua, B., Abderrahmani, A., Gasbaoui, B., & Nasri, A. (2008). The efficiency of particle swarm optimization applied on fuzzy logic dc motor speed control. Serbian Journal of Electrical Engineering, 5(2): 247-262.

Clerc, M., & Kennedy, J. (2002). The particle swarm-explosion, stability and convergence in multidimensional complex space. IEEE Trans. On Evolutionary computation, 6(1): 58-73.

Dorigo, M., & Stützle, T. (2004). Ant colony optimization. MIT Press, Cambridge, MA:

Gupta, V. K., Tiwari, B., & Dewangan, B. (2015). Efficiency optimization of induction motor drive: a review. International Journal of Innovative Science, Engineering & Technology, 2(12): 650-665.

Issa, R. (2013). Separately excited dc motor optimal efficiency controller. International Journal of Engineering and Innovative Technology, 3(1): 533-539.

Kennedy, J., & Eberhart, R. C. (1995). Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Networks, 4, 1942– 1948.

Kikpatrick, S., Gelatt Jr., C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing, Science, 220, 671-680.

Kusko, A., & Galler, D. (1983). Control means for minimization of losses in ac and dc motor drives. IEEE Trans. Industry Applications, IA-19(4): 561-570.

Lim, S., & Nam, K. (2004). Loss-minimizing control scheme for induction motors. Proceedings of IEE on Electric Power Application, 151(4): 385–397.

Łukasik, S., & Żak, S. (2009). Firefly algorithm for continuous constrained optimization tasks. International conference on computational collective intelligence, Springer, Berlin, Heidelberg, 97-106.

Mishra, A. K., & Narain, A. (2013). Speed control of dc motor using particle swarm optimization. International Journal of Engineering Research & Technology, 2(6): 1643-1649.

Optimization. In The Merriam-Webster.com Dictionary. Retrieved October 20th, 2019, from https://www.merriam-webster.com/dictionary/optimization.

Rashtchi, V., Bizhani, H. (2015). Using of particle swarm optimization for loss minimization of vector-controlled induction motors. Universal Journal of Electrical and Electronic Engineering, 3(3): 71-80.

Tyo, T. M., Airoboman, A. E., Amaize, P. A., & Idiagi, N. S. (2016). Losses optimization of induction motor using genetic algorithm. International Journal of Engineering Sciences & Research Technology, 5(2): 644-648.

Yoshida, H., Kawata, K., Fukuyama, Y., Takayawa, S., & Nakanishi, Y. (2000). A particle swarm optimization for reactive power and voltage control considering voltage security assessment. IEEE Trans. on Power systems, 15(4): 1232-1239.

Published
2019-12-31
How to Cite
Airoboman , A., Ahmed , H., Ibrahim, S. O., Salihu, H. A., Gatta, C., & Chime, D. (2019). Losses Optimization of Induction Motor using Particle Swam Optimization Technique . Advances in Electrical and Telecommunication Engineering (AETE) ISSN: 2636-7416, 2(2), 55 - 62. Retrieved from https://sciengtexopen.org/index.php/aete/article/view/63
Section
Articles