Open AccessPower loss minimization load flow studies using Artificial Bee Colony swarm intelligence technique
Author(s) -
Z.O. Jagun,
Matthew B. Olajide,
Biobele A. Wokoma,
Emmanuel N. Osegi
Publication year - 2021
Publication title -
nigerian journal of technology
Language(s) - English
Resource type - Journals
eISSN - 2467-8821
pISSN - 0331-8443
DOI - 10.4314/njt.v40i4.19
Subject(s) - artificial bee colony algorithm , swarm intelligence , context (archaeology) , port harcourt , power (physics) , minification , engineering , electric power system , swarm behaviour , computer science , particle swarm optimization , mathematical optimization , mathematics , artificial intelligence , biology , physics , paleontology , quantum mechanics , socioeconomics , sociology
This paper presents the capability of an emerging swarm intelligence technique for power loss minimization known as the Artificial Bee Colony (ABC) used in the context of an Alternative Load Flow Analysis (LFA) technique (ABC-LFA) for the solution of a power systems network. Studies are performed considering the effect of an important parameter of the ABC, the “maxcycle” on the LFA process; experiments are conducted by applying the ABC-LFA to the Western System Coordinated Council (WSCC) 3-machine 9- bus power system and a section of the Nigerian 132-kV power transmission network Port-Harcourt Region (NPHC-132), and the results reported. The results indicate that increasing the value of the ABC “maxcycle” parameter has a pronounced effect on the results obtained by the ABC-LFA. The results also indicate the sensitivity of the ABC to low values of maxcycle parameter.