Acta Marisiensis.
Seria Technologica



ISSN 2668-4217
ISSN-L 2668-4217
(Online)


Română

HomeEditorial boardSubmit paperPublication ethicsContactIndexing
Year 2024
Volume 21 (XXXVIII), no 1

Year 2023
Volume 20 (XXXVII), no 1
Volume 20 (XXXVII), no 2

Year 2022
Volume 19 (XXXVI), no 1
Volume 19 (XXXVI), no 2

Year 2021
Volume 18 (XXXV), no 1
Volume 18 (XXXV), no 2

Year 2020
Volume 17 (XXXIV), no 1
Volume 17 (XXXIV), no 2

Year 2019
Volume 16 (XXXIII), no 1
Volume 16 (XXXIII), no 2

Year 2018
Volume 15 (XXXII), no 1
Volume 15 (XXXII), no 2

Year 2017
Volume 14 (XXXI), no 1
Volume 14 (XXXI), no 2

Year 2016
Volume 13 (XXX), no 1
Volume 13 (XXX), no 2

Year 2015
Volume 12 (XXIX), no 1
Volume 12 (XXIX), no 2

Year 2014
Volume 11 (XXVIII), no 1
Volume 11 (XXVIII), no 2

Year 2013
Volume 10 (XXVII), no 1
Volume 10 (XXVII), no 2

Year 2012
Volume 9 (XXVI), no 1
Volume 9 (XXVI), no 2

Year 2011
Volume 8 (XXV), no 1
Volume 8 (XXV), no 2

Year 2010
Volume 7 (XXIV), no 1
Volume 7 (XXIV), no 2

Year 2009
Volume 6 (XXIII)

2022, Volume 19 (XXXVI), no 2

Optimal Reactive Power Dispatch Using Improved Chaotic PSO Algorithm with the Wingbeat Frequency

Author(s):
Sunday ADETONA, Michael JOHN, University of Lagos, Nigeria
Salmar UMAR, Columbia University, New York, United States of America

Abstract:
The importance of reactive power to the economy and security of power systems cannot be overemphasized. For instance, Transmission losses increase when reactive power is unevenly distributed on transmission network; and power quality is affected as well. The cheapest way of reducing these transmission lines losses is via reactive power dispatch approach. This study therefore proposes an Improved Chaotic Particle Swarm Optimization algorithm (ICPSO) with the primary aim of reducing real power transmission line losses while adhering to system constraints. Although the traditional PSO has a fast convergence speed, it falls easily into local optimum and it is slow at the later stage of convergence. The ICPSO is proposed in this research to overcome these shortcomings. The approach combines PSO with chaotic map which increases particles’ diversity, allowing particles to explore the search region more; and a wingbeat frequency component which helps to sustain the rate of convergence of particles. MATPOWER 7.1 in MATLAB 2019a environment was utilized for the implementation. The purported algorithm was examined on IEEE14 and IEEE30 Test Beds respectively. When tried out on IEEE14 Test bed, real power loss was reduced from 13.393 MW to 12.260 MW; whereas real power transmission line loss was brought down from 17.557 MW to 15.977 MW when tried out on IEEE30 Test Bed. In terms of reducing real power transmission lines losses, the simulation results show that the proposed approach performs better when compared with other algorithms.

DOI: https://doi.org/10.2478/amset-2022-0013

Pages: 20-29

View full article
Update: 19-Jun-2024 © Published by University Press