Multiconverter unified power quality conditioning system using Artificial Neural Network technique

Abstract

This paper presents a new unified power-quality conditioning system (MC-UPQC), capable of simultaneous compensation for voltage and current in multibus/multifeeder systems. In this configuration, one shunt voltage-source converter (shunt VSC) and two or more series VSCs exist. The system can be applied to adjacent feeders to compensate for supply-voltage and load current imperfections on the main feeder and full compensation of supply voltage imperfections on the other feeders. In the proposed configuration, all converters are connected back to back on the dc side and share a common dc-link capacitor. Therefore, power can be transferred from one feeder to adjacent feeders to compensate for sag/swell and interruption. The performance of the MC-UPQC as well as the adopted control algorithm is illustrated by simulation. The present work study the compensation principle and different control strategies used here are based on PI & ANN Controller of the MC-UPQC in detail. The results obtained in MATLAB/PSCAD on a two-bus/two-feeder system show the effectiveness of the proposed configuration.Index Terms-power quality (PQ) unified power-quality conditioner (UPQC), voltage-source converter (VSC),Aritifical neural network-ANN.

Performance analysis of multiconverter unified power quality conditioner with an EPLL-based controller at medium voltage level

“…The total harmonic distortion is decreased from 25.08% to less than 5%, and the PI‐controlled DC link capacitor voltage ( U dc ) is kept around 1.7 kV. The transient response of PI controller is faster than the fuzzy logic‐based controller in Paduchuri et al Besides, the lower total harmonic distortion is obtained by EPLL, unlike the artificial neural network‐based controller used in Saaki et al Reactive powers of injected ( Q pf ), source ( Q s 1 ), and load ( Q l 1 ) are also demonstrated in Figure . Reactive power is compensated by injecting an average of 103 kVA during the case study.…”