IMPLEMENTING ARTIFICIAL NEURAL NETWORK BASED DVR TO IMPROVE POWER QUALITY OF RUMUOLA-RUMUOMOI 11kV DISTRIBUTION NETWORK

The most vexing problem plaguing Rumuomoi's 11kV distribution network is voltage sag and swell, which degrades power quality. There has been no effective mitigation control implemented. purpose of this research to address the issue quality by implementing artificial neural (ANN) with an embedded dynamic restorer (DVR). To begin, trained using input desired data obtained during simulation a proportional integral (PI) controller. limit amount training, Levenberg-Marquardt feed forward back method utilized, result for each iteration determined in Matlab software. system was tested replicated model Rumuomoi it that Bus 7 0.938p.u, 8 0.9244p.u, 9 0.9148p.u, 10 0.9035p.u, 11 0.8912p.u, 12 0.8811p.u, all exceeded statutory condition 0.95-1.01p.u. were bus violations after optimization DVR, demonstrating DVR at enhancing removing swell network.