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Faults in the power system generally provide considerable changes in its quantities such as under or overpower , over-current, current or power direction, frequency, impedance, and power factor. Reading data related to both currents and voltages is usually involved for detecting and situating the fault on the transmission network. These days, any outage of power in a power grid leads to heavy financial losses for commercial, industrial, and domestic consumers. Random and irregular faults in transmission grids contribute significantly to events of power outages. A significant contribution of this study is a new technique for simulating a multiple simultaneous faults model. The recommended approach is an effective technique for detection, classification and localization of faults in transmission networks of electric power. To attain this objective, a training procedure and a neural network simulation were carried out using m-file in MATLAB. A virtual bus has been proposed to analyze the fault which happens on the transmission line and bus. This technique has been applied on the IEEE 14 bus and multiple simultaneous faults have been mentioned in this study. The fault situations are simulated in m-files through the two-port network performance method, which is a highly enhanced scheme in comparison to the existing methods. The results have been arrived upon by subjecting different buses to varying types of fault. The results provide comprehensive information regarding fault current, post-fault voltages, and fault MVA on all the buses. The values at the bus for voltage, power consumption, and phase angles were specified. As suggested by the findings of the simulation, the proposed methodology is an effective technique for detection, classification and localization of faults

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