Optimal Placement of Grid-Forming Inverters in Low Inertia Power Systems Using Bacterial Foraging Optimization

The shift towards renewable energy in modern power systems introduces significant challenges due to the reduction in system inertia traditionally provided by synchronous generators. This lack of inertia increases the risk of frequency instability, characterized by high rates of change of frequency (RoCoF) and more significant frequency deviations during disturbances. However, there is hope in the form of gridforming inverters, which offer a promising solution by providing synthetic inertia and stabilizing frequency independently of grid conditions. The strategic placement of these inverters is crucial for maximizing their impact on system stability. This study introduces an optimization framework using Bacterial Foraging Optimization (BFO) to identify optimal placement strategies for grid-forming inverters in lowinertia power systems. The BFO algorithm, derived from the foraging behavior of E. coli bacteria, is utilized to improve system stability measures, such as the smallest eigenvalue of the reduced Laplacian matrix and the H2 norm. Simulation results on benchmark power systems demonstrate that BFO-optimized placements significantly improve stability by increasing the smallest eigenvalue by up to 25% and reducing RoCoF by approximately 20% compared to random placements.