Fault optimisation on IEEE 14-bus system with machine learning-based SPLIT TCSC Online publication date: Sun, 14-May-2023
by Niharika Agrawal; Faheem Ahmed Khan; Mamatha Gowda
International Journal of Power and Energy Conversion (IJPEC), Vol. 13, No. 3/4, 2022
Abstract: All the operations of the power system should be smooth, continuous, reliable, and efficient. An electric fault interrupts the normal flow of power, damages the electrical equipment, creates abnormal voltages and currents, and deteriorates the system's power quality. In this manuscript, a novel device, the SPLIT TCSC, is implemented with the traditional proportional-integral (PI) controller and with controllers based on machine learning algorithms such as artificial neural network, and random forest for fault optimisation on IEEE 14-bus system. These controllers showed better results than the PI controller with respect to voltage during fault time and THD reduction. The voltage drop is around 30 kV, and the THD is around 1.95% with the system based on random forest. The results showed that power is utilised more effectively with the application of these algorithms in the system, along with improvements in the power quality, reliability, and efficiency of the system.
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