Cover
Vol. 24 No. 2 (2024)

Published: August 31, 2024

Pages: 74-78

Original Article

Using PSO Algorithm to Find Optimal Number and Location by Connecting Distribution Generators to Improve the Iraqi 400 kV Super Grid

Dunya Sh. Wais 1 Huda A. Abbood 1 Ali F. Hassoon 1
1 Department of Electrical Engineering, College of Engineering, University of Al-Mustansiriyah, Baghdad, Iraq
History
  • Received: January 13, 2024
  • Revised: April 23, 2024
  • Accepted: May 4, 2024
  • Available Online: August 17, 2024
DOI

https://doi.org/10.33971/bjes.24.2.10

Abstract

Nowadays, it is crucial to assess power system contingencies resulting from line outages or generator failures, as they might cause breaches of system constraints. This is a vital part of ensuring the security of modern power supplies. Another hindrance to providing electricity to consumers is the increased system losses and voltage fluctuations resulting from increased demand and diminished power generation capacity. The DG connection is a crucial subject regarding these harmful consequences. This study is focused on clarifying the effect of distribution generators (DG) on mitigating congestion in electrical power transmission lines, minimizing power losses, and enhancing the voltage profile of the Iraqi national grid system. An optimization method is used to identify the optimal size and position based on fitness indicators such as voltage, power losses, and line congestion. The PSO algorithm is executed as proposed. The outcomes illustrate the effectiveness of the proposed technique for estimating the optimal size and placement of distributed generators (DG). At the same time, it reduces congestion and improves the voltage level of the bus. The proposed technique was implemented using the MATLAB/R2018a programming language.

Keywords

References

  1. S. G. B. Dasan, S. S. Ramalakshmi and R. P. Kumudini Devi, “Optimal siting and sizing of hybrid Distributed Generation using EP,” 2009 International Conference on Power Systems, Kharagpur, India, pp. 1-6, 2009.
  2. P. Khetrapal, “Distributed Generation: A Critical Review of Technologies, Grid Integration Issues, Growth Drivers and Potential Benefits”, International Journal of Renewable Energy Development, Vol. 9, Issue 2, pp. 189205, 2020. https://doi.org/10.14710/ijred.9.2.189-205
  3. P. S. R. Murty, Power System Analysis, Second Edition, Elsevier Ltd., USA, 2017.
  4. L. L. Grigspy, Power Systems, Third Edition, CRC Press Tylor & Francis Group, London, 2012.
  5. P. Kundur, Power System Stability and Control, Mc GrawHill Professional Publishing, New York, 1994.
  6. I. Dobson and D. E. Newman, “Cascading blackout overall structure and some implications for sampling and mitigation”, International Journal of Electrical Power & Energy Systems, Vol. 86, pp. 29-32, 2017.
  7. J. A. Refaee, M. Mohandes and H. Maghrabi, “Radial basis function networks for contingency analysis of bulk power systems,” IEEE Transactions on Power Systems, Vol. 14, No. 2, pp. 772-778, 1999.
  8. D. Asija, P. Choudekar, “Congestion management using multi-objective hybrid DE-PSO optimization with solaress based distributed generation in deregulated power Market,” Renewable Energy Focus, Vol. 36, pp. 32-42, 2021. https://doi.org/10.1016/j.ref.2020.10.006
  9. B. Sun, Y. Li, Y. Zeng, J. Chen, and J. Shi, “Optimization planning method of distributed generation based on steadystate security region of distribution network”, Energy Reports, Vol. 8, pp. 4209-4222, 2022.
  10. E. Dehnavi, F. Aminifar, S. Afsharnia, “Congestion management through distributed generations and energy storage systems,” International Transactions on Electrical Energy Systems, Vol. 29, Issue 6, 2019.
  11. K. Muthulakshmi, R. M. Sasiraja, V. S. Kumar, “The Phenomenal Alleviation of Transmission Congestion by Optimally Placed Multiple Distributed Generators Using PSO”, Circuits and Systems, Vol. 7, Issue 8, pp. 16771688, 2016. https://doi.org/10.4236/cs.2016.78145
  12. Y. Y. Zakaria, R. A. Swief, N. H. El-Amary, and A. M. Ibrahim, “Optimal Distributed Generation Allocation and Sizing Using Genetic and Ant Colony Algorithms”, IOP Publishing, Journal of Physics: Conference Series, Vol. 1447, No. 1, 2020.
  13. H. Saadat, Power system analysis, McGraw-Hill, Vol. 2, 1999.
  14. L. Al-Bahrani, and V. Dumbrava, “Optimal Power Flow Based on Particle Swarm Optimization”, University Politehnica of Bucharest Scientific Bulletin Series CElectrical Engineering and Computer Science, Vol. 78, Issue 3, pp. 253-264, 2016.
  15. M. A. Abdulsada, F. M. Tuaimah, “Power System Static Security Assessment for Iraqi Super High Voltage Grid”, International Journal of Applied Engineering Research, Vol. 12, Issue 19, pp. 8354-8365, 2017.