Voltage profile enhancement in grid system using expert system

Frequent and severe blackouts are been attributed to insufficient voltage stability, resulting in voltage collapse. To mitigate this issue and ensure adequate voltage stability and damping in power systems, this study explores smart grid solutions. The proposed control strategies are applied to a distribution static synchronous compensator (DSTATCOM) within a multi-machine system. The recommended approach, radial basis function neural network (RBFNN)-DSTATCOM with support vector machine (SVM), incorporates a PI controller to minimize system deviations. The damping performance of the RBFNN-DSTATCOM controller is analyzed against a fixed-parameter proportional-integral (PI)-DSTATCOM controller. Simulation analysis indicates that the proposed RBFNN-DSTATCOM controller effectively enhances power system stability under various disturbances and operating conditions. Critical bus graphs are provided for scenarios both with and without the DSTATCOM. A parametric evaluation is conducted using the 'powergui' toolbox based on the system's standard ratings. Finally, a comparative analysis is presented, utilizing the results from both systems, with all graphs plotted against time using the power system analysis toolbox (PSAT) in MATLAB.