Robust Iteration-dependent Least Mean Square-based Distribution Static Compensator Using Optimized PI Gains

A robust iteration-dependent least mean square (RIDLMS) algorithm-based fundamental extractor is developed to estimate the components of load current for a four-wire DSTATCOM with nonlinear load. The averaging parameter calculating variable step size iteration dependent and uses tuning parameters. Rather than using value, previous learning rate was used in this method achieve more adaptive solution. This additional control factor aids determining exact rate, resulting reliable convergent outcomes. Its faster convergence avoidance local minima make it advantageous. estimation PI controller gains achieved through self-adaptive multi-population algorithm. change group number will increase exploration exploitation. nature algorithm determine subpopulation needed according fitness value. main advantage spread throughout search space better optimal estimated controllers are DC bus AC terminal voltage error minimization. RIDLMS-based obtained proposed optimization showed power quality performance. considered RIDLMS-supported demonstrated experimentally d-SPACE-1104.