TY - JOUR N2 - The electrical grid integration takes great attention because of the increasing population in the nonlinear load connected to the power distribution system. This manuscript deals with the power quality issues and mitigations associated with the electrical grid. The proposed single comprehensive artificial neural network (SCANN) controller with unified power quality conditioner (UPQC) is modelled in MATLAB Simulink environment. It provides series and shunt compensation that helps mitigate voltage and current distortion at the end of the distribution system. Initially, four proportional integral (PI) controllers are used to control the UPQC. Later the trained SCANN controller replaces four PI Controllers for better control action. PI and SCANN controllers’ simulation results are compared to find the optimal solutions. A prototype model of SCANN controller is constructed and tested. The test results show that the SCANN based UPQC maintains grid voltage and current magnitude within permissible limits under fluctuating conditions. L1 - http://journals.pan.pl/Content/122220/PDF-MASTER/BPASTS_2022_70_1_2494.pdf L2 - http://journals.pan.pl/Content/122220 PY - 2022 IS - 1 EP - e140257 DO - 10.24425/bpasts.2022.140257 KW - SCANN KW - UPQC KW - total harmonic distortion KW - particle swarm optimization A1 - Balaji, Varadharajan A1 - Chitra, Subramanian VL - 70 DA - 25.02.2022 T1 - Power quality management in electrical grid using SCANN controller-based UPQC SP - e140257 UR - http://journals.pan.pl/dlibra/publication/edition/122220 T2 - Bulletin of the Polish Academy of Sciences Technical Sciences ER -