Experimental Investigations on Particle Swarm Optimization Based Control Algorithm for Shunt Active Power Filter to Enhance Electric Power Quality

Quality power is a very important factor for the proper functioning of appliances and can be enhanced using shunt active power filters (SAPF). This work demonstrates the hardware implementation of synchronous reference frame (SRF) theory based SAPF. This paper presents the technique of particle swarm optimization (PSO) to tune the gain values of the SAPF PI controller to control the voltage of the DC-link and enhance its dynamic efficiency. The estimation of gain values of PI controllers using conventional methods does not yield the expected outcomes under varying load conditions. The PSO tuned controller provides better results as compared to traditional tuning methods. The switching scheme is implemented using hysteresis controller to control the SAPF. The main objectives of this approach are to extract the compensating currents and cancel out the harmonics produced by balanced, unbalanced and nonlinear loads. The planned scheme is designed and implemented in MATLAB/Simulink and then its performance on a developed laboratory prototype is validated experimentally.

Automated summary

This paper presents the hardware implementation of a shunt active power filter (SAPF) based on synchronous reference frame (SRF) theory. The gain values of the SAPF PI controller are tuned using particle swarm optimization (PSO) technique to enhance its dynamic efficiency. Experimental results show that the PSO tuned controller provides better performance compared to traditional tuning methods.