A Comparative Study Of ILST and ANN Algorithm for Control of DSTATCOM

The subject of the paper is concerned with the simulation and conception of a DSTATCOM using an Artificial Neural Network (ANN) algorithm for controlling an IGBT- based Voltage Source Converter (VSC) for a 3∅-3wire system. The system feeds different loads through the controller, which is accustomed to mitigating power quality complications such as harmonics, unbalance in grid currents, and reactive power. Conventional regulators/control algorithms being fixed design gives ideal execution or result just over a restricted scope of working conditions for which they are planned. Alternative regulators are dependent on neural networks and fuzzy logic, which are sturdier and can be intended to work well under a broad scope of operating conditions. The results of Improved Linear Sinusoidal Tracer (ILST), and Artificial Neural Network (ANN) is presented to show the efficacy of later by simulating the system in MATLAB software using Simscape blockset and their comparison is conferred. The total harmonic distortions of source current and source voltage are estimated which are under IEEE-929 and IEEE-519 guidelines.