Biogeography based optimization strategy for upqc pi tuning on full order adaptive observer based control

Abstract

Adaptive full order observer based control algorithm for unified power quality conditioner is presented. The full order adaptive observer based algorithm is capable of estimating fundamental positive sequence components parameters, including frequency, amplitude, and phase form power supply systems. Due to its adaptive response, monitoring accuracy, and faster detection of fundamental positive sequence components under all different loads and grid conditions, it is used for power quality improvement. In addition to full order adaptive observer based control algorithm, a biogeography-based optimization method is employed here for tuning the Kp and Ki gains of a proportional integral controller on unified power quality conditioner system. The proposed method minimizes the dc-link voltage oscillations and enhances its step response by optimally tuning the proportional integral controller. This is done by reducing the objective function of the integral time absolute error for different power quality perturbations. The numerical values obtained by biogeography based optimization are selected as proportional integral gains and it also improves the controller’s performance. The full order adaptive observer control integrated with biogeography based optimization algorithm is tested interface with MATLAB/Simulink on developed unified power quality conditioner under different power quality problems at different intervals. The performance results demonstrate the quick convergence rate with effective performance.