Voltage stability enhancement based optimal reactive power control

Power system networks are exposed to various environmental and economic challenges that can have a detrimental impact on their stability and capacity to provide a consistent power supply, particularly in developing countries. The voltage stability monitoring is crucial for the system's status and capability to provide an uninterrupted power supply. Delayed responses to voltage instability can significantly damage the power grid system, making it essential to take prompt and appropriate action to mitigate voltage instability and ensure the system's safe and efficient operation. This paper proposes two approaches to enhance the stability of power systems. A neural network employing feedforward backpropagation to detect the critical bus in the IEEE 9-bus system based on Voltage Stability Index Lmn and loadability Index. The FFBPNN identifies the critical bus prone to voltage collapse in the power system, trained using a backpropagation algorithm. The second approach utilizes an optimization technique based on Particle Swarm Optimization PSO to optimize the reactive power control of a Static Var Compensator SVC device through its size and location, where the SVC device considers a type of Flexible AC Transmission System FACT device. This approach minimizes the reactive power effect which causing of voltage instability during high load demand, improving the voltage stability of the system. The proposed method is evaluated under different load levels and network configurations and validated based on the Newton-Raphson method for optimal power flow analysis.