Enhanced particle swarm optimization technique for interleaved inverter tied shunt active power filter

This paper proposes an advanced search-based enhanced particle swarm optimization technique (EPSO) for interleaved inverter tied shunt active power filter (SAPF) to tune the integral and proportional (PI) controller gain values. The present power system is connected with inevitable nonlinear loads which cause harmonic pollution in the system. The unpredictable loses of interleaved inverter tied SAPF like switching loses, inductor power losses have to be supplied by DC-link capacitor under steady-state operation and load real power during transient condition of the load. This is effectively controlled by the PI controller to maintain the reference value under any circumstances. Conventionally, PI gain values had been tuned by the linearized model of SAPF. However, this technique gives inadequate results under voltages and transient condition of the loads. The soft computing techniques play a tremendous role in optimization of the gain parameters of PI controller values. The EPSO reduces the search process to obtain the best position which reduces the convergence time, memory and improves the convergence speed compared to conventional PSO. The complete system is modeled using MATLAB/Simulink software to show the comparative analysis of analytical PI, conventional PSO, and EPSO performance under the steady-state and transient condition of nonlinear loads. The simulation results have been validated by developing the hardware prototype model in the laboratory using dSPACE1104 controller. Complete results have been presented.