ALO-optimized artificial neural network-controlled dynamic voltage restorer for compensation of voltage issues in distribution system

The major concern in power distribution system is the power quality concerns specifically voltage sag/swell and harmonics. To compensate for such voltage disturbances, an effective device called dynamic voltage restorer (DVR) is utilized in the electric power distribution system. Accordingly, in this paper, the DVR is designed to shield the sensitive load from source-side voltage disturbances under nonlinear load conditions. Further, in the proposed work, an ant lion optimizer-optimized artificial neural network (ALO-ANN) is used to control DVR, thus compensating the balanced and the unbalanced voltage sag/swell and distortions in the load-side voltage. Simulation results using MATLAB/Simulink software are analysed to confirm the efficiency of the suggested ALO-ANN regulator scheme of DVR system at critical loads by comparing with the existing PSO (particle swarm optimization)-centred control scheme.