Application of Advanced Soft Computing Techniques for Power Quality Improvement Using Active Power Filters in Radial Distribution System

Abstract

This paper investigates the application of advanced soft computing techniques: northern goshawk optimization (NGO) and coati optimization algorithm (COA) for improving power quality (PQ) using active power filter (APF) in radial distribution systems (RDS). While beneficial, the growing adoption of solar photovoltaic (SPV) systems introduces power quality concerns like harmonic distortion due to their nonlinear nature. This distribution generator (DG) type is called nonlinear DG (NLDG). Harmonics is the leading cause of poor PQ. This study considers nonlinear loads (NLs) at two end nodes and nonlinear DG (NLDG) integrated into the RDS. APFs are optimally placed to reduce the harmonics and enhance PQ. The proposed approach utilizes soft computing techniques to minimize the APF current while adhering to inequality constraints. The NGO, inspired by natural processes, is employed for optimal APF sizing. This method prioritizes a balance between exploration and exploitation for efficient searching. The effectiveness of NGO is evaluated through simulations on the IEEE-69 bus RDS and compared with another recent soft computing technique, the COA. Here, four different cases are considered: a) only NL+NLDG, b) APF at bus 27, c) APF at bus 35, and d) APFs are at 27 and 35 buses. These cases are considered to analyze the effect of placement and sizing of APFs on PQ in RDS. The results validate the stability and efficacy of NGO in addressing this optimization problem for PQ improvement in RDS.