Journal of Engineering Research and Reports

Voltage instability remains a critical operational concern in the Nigerian 330 kV transmission network, particularly under disturbances and increasing loading. This study evaluated voltage-stability improvement in selected substations within the south-western region using a unified power flow controller (UPFC) and an artificial neural network (ANN). A five-bus representation comprising Egbin GS, Okearo TS, Aja TS, Akangba TS, and Ikeja West TS was modelled in the Power System Analysis Toolbox (PSAT), while MATLAB/Simulink was used for the analysis of power-flow and dynamic-voltage responses. Newton-Raphson power-flow analysis was applied to determine line active power losses and identify the controller-placement location. Line 3, connecting bus 1 (Egbin GS) to bus 5 (Ikeja West TS), recorded the highest active power loss of 0.1084 pu and was selected for UPFC and ANN allocation. Following implementation, the bus voltage profiles were improved to the stated operating range of 0.95–1.05 pu. The dynamic responses also showed reduced oscillations and shorter settling behaviour under both control approaches. Using the voltage stability index reported in the study, the ANN achieved 97%, whereas the UPFC achieved 93%. Under the specific simulation conditions considered, the ANN therefore produced the higher reported VSI and a smoother voltage response. The findings are limited to the model configuration and operating conditions evaluated in this study.