Improving the security of the Nigeria 330kv grid network using intelligent margin and sensitivity-controlled fact devices

Subject Area: POWER SYSTEM

This study aimed to enhance the security of Nigeria's 330kV grid network through the implementation of intelligent margin and sensitivity-controlled FACT devices. Reviewing existing literature revealed a gap in the development of a comprehensive system capable of effectively managing load and stabilizing the grid to prevent collapse. To address this challenge, a top-down design methodology was employed, beginning with problem formulation via characterization using Newton-Raphson load flow analysis. Subsequently, an extreme learning-based algorithm was developed and trained using data collected from the 5Bus, 330kV transmission network to generate margin and sensitivity algorithms. These algorithms were integrated with a Universal Power Flow Controller (UPFC) to create an intelligent UPFC, serving as a controller for load management and grid stabilization. Simulation tests on the 330kV transmission network demonstrated voltage magnitude within the Nigerian Electricity Regulatory Commission (NERC) standards for stability, and phase angle evaluations indicated a stable network. System integration of the intelligent UPFC on the 5Bus network yielded promising results, with an average voltage magnitude of 0.996903pu and a phase angle of -13.6728 degrees, affirming grid stability. Comparative analysis showcased notable improvements, including a 5.7% enhancement in voltage magnitude stability and a 52.15% increase in power control stability with the implementation of the intelligent UPFC.