Bi-level multi-objective optimization of harmonic filters for PV penetration and harmonics mitigation in power distribution using Autism-based optimizer

Abstract

The rising usage of power electronic converters linked to renewable energy sources has become a major source of harmonics in power systems. Passive harmonic filters are an excellent solution for addressing this issue. However, these traditional filters have a problem linked to resonance frequency, which needs damping. This paper introduces a Harmonic Blocking Filter (HBF) that consists of a shunt-connected Damped Double-Tuned Passive Filter (DDTF) and a series component. Six different DDTF schemes are investigated: four single-resistor DDTFs (SR-DDTF) and two double-resistor DDTFs (DR-DDTF). This study intends to perform harmonic mitigation and increase PV penetration levels by obtaining parameters for each HBF system using the Autism-Based Optimizer (ABO). The Harmonic Pollution Factor (HPF) is a power quality indicator used to assess and reduce the system’s harmonic content. The findings show that the proposed HBF filter efficiently increases PV penetration in the system while lowering harmonic levels.