Steady state Power Flow improvement on Nigerian 33kV network using ANN control mechanism

Abstract

The critical infrastructure that links the transmission system and the distribution network was the 33kV network feeders and that has always been the case in the Nigerian power system network. hence, damage on the 33kV systems means a cut off in power flow and electricity distribution to end users. Hence, to ensure functionality of the power system, ANN was introduced to improve the power quality of the system. The network utilized was a 33kV feeder in Owerri Imo state, Nigerian comprising of 7-buses and 7-lines. the system was modeled in PSAT and the simulated voltage and current signal was utilized for the configuration of the artificial neural network (ANN) model and was utilized as a control system in the power system network. to obtain the strategic location for the ANN implementation, the ANN was placed on all the lines sequentially, from the results obtained, it was seen that the optimum (minimum) active and reactive loss of 0.5552pu and 0.614pu respective at line 4. The percentage improvement achieved for the voltage profile, active flow, reactive flow, active loss and reactive loss were 12%, 19%, 22%, 18% and 21.3% respective. The paper has proved that ANN is effective in improving the steady state power quality of a 33kV power system.