This paper presents the dynamic responses of generators in a multi-machine power system.  The fundamental swing equations for a multi-machine stability analysis are revisited. The swing equations are solved to investigate the influence of a three-phase fault on the network largest load bus. The Nigerian 330kV transmission network was used as a test case for the study. The time domain simulation approach was explored to determine if the system could withstand a 3-phase fault. The stability of the transmission network is estimated considering the dynamic behaviour of the system under various contingency conditions. This study identifies Egbin, Benin, Olorunsogo, Akangba, Sakete, Omotosho and Oshogbo as the key buses within the network, which could provide useful information when a three-phase fault occurs on Ikeja-West (Bus with the largest load). The results obtained also show that the system loses synchronism immediately a three-phase fault was simulated on the largest load bus, considering various contingencies with the generator at Geregu being the most severely disturbed generator.

The rapid growth in the demand for electrical energy due to the astronomic growth in population has led to increase in the system fault current levels. This increase in fault current if not properly checked, could lead to system collapse. Superconducting Fault Current Limiters (SFCLs) are used in power system networks to mitigate against high fault current levels. In this study, the transient stability enhancement capability of three commercially available Resistive-type Superconducting Fault Current Limiters (R-SFCLs) based on Yttrium-Barium-Copper-Oxide (YBCO) and Bismuth-Strontium-Calcium-Copper-Oxide (BSCCO) Coated Conductors of different lengths were simulated. The test case was the Nigeria 330kV transmission network. The Runge-Kutta method was used to solve the differential equations characterizing the swing equations of the generators. The proposed method shows the effectiveness of the SFCL in enhancing transient stability of a Multi-Machine System.