Intelligent control model to enhance the performance of unified power quality conditioner

A unified power quality conditioner (UPQC) has two converters interlinked with back to back DC voltage source. The UPQC is used to improve the multiple power quality (MPQ) of the AC distribution network. The quality of the UPQC depends on the selection of series and shunt control algorithms. The series converter injects the voltage and improves voltage quality whereas the shunt converter injects current and improves the current quality of the AC distribution network. The UPQC works properly if the DC link voltage maintains constant under abnormal or normal condition of AC grid system. Thus, in this paper, DC link voltage is controlled using intelligent model, adaptive neuro fuzzy inference system (ANFIS). The ANFIS result is compared with fuzzy model and conventional PI controller to enhance the mitigation capability of the UPQC. Moreover, the series and shunt converters are controlled by modified second order generalised integrator (SOGI) based algorithm. The performance of intelligent control model is verified by MATLAB based simulation results.