Okachi, S. E., Akpama, E. J, Pepple, E. C., Acha, G.o
In the Nigerian Power Sector (Lagos Zone), the deregulation exercise and constant rise in Load demand has led to the need for planning, controlling and expanding of the power system network which is important and it’s done with power flow studies on existing network to determine some unknown network parameters with the assumptions that the system is in steady state. In this work, ABC simulates the intelligent foraging behaviour, of a honeybee swarm and it is used for optimizing a large set of numerical test functions and the results produced by the three variants of the ABC namely, ABC_normal, ABC_global best and ABC_matlab fitness evaluation controlled. They are investigated to ascertain which is best or which of these technique are potential candidates used for load flow analysis of power system network? Simulations were conducted using the MATLAB programming language considering primarily the bus voltage, line losses and phase angle for the 35bus, 132kV Nigerian sub-transmission power system network, Lagos Zone. The results of simulations revealed that the voltages and angles solved by the ABC_normal and ABC_gbest techniques are closely correlated i.e. not significantly different from zero, with a p-value of about 0.3033 and 0.2029 respectively with the Pearson T-test; and on the other hand, there exists no correlation between the ABC_normal and ABC_mfe_controlled technique corresponding to a significant distance from zero. The ABC_gbest also fared better giving the least cost or power mismatch after 15,000 iterations of the load flow simulation.
Artificial Intelligence, Artificial Bee Colony, Load Flow Analysis, Employed Bees
Cite this paper
Okachi, S. E., Akpama, E. J, Pepple, E. C., Acha, G.o. (2022) Load flow analysis of 132KV Transmission System Using Artificial Bee Colony Algorithm. International Journal of Computers, 7, 31-37