Real-Time Implementation of ALMS-NN Controlled UPQC

Abstract

This paper presents an ALMS-NN (Adaptive Least Mean Square Neural Network) controller based algorithm strategy for the three phase three wire (3p3w) Unified power quality conditioner (UPQC) system. The vital aim of active power conditioning is to manage disparate power quality apropos issues such as mitigation of harmonics in both current as well as voltage, voltage balancing and voltage regulation, compensation of reactive power and power factor correction (PFC) in the power distribution network. An adaptive control algorithm (ALMS-NN) is carried out to extract the compensating reference source currents for shunt and instantaneous p-q control theory to extract the reference source voltage for series active power filters (APFs) of UPQC. Moreover, the voltage source converters (VSC) of the UPQC are triggered by using these reference currents and voltages and performances are compared under uneven loading conditions. The effectuality of the ANN controller algorithm is depicted on the basis of mathematical equation with in-depth simulation study by applying MATLAB/SIMULINK tool in parallel with real-time implementation by RTDS (real time digital simulator).