Jellyfish Search Algorithm-Based Optimization of C-Type Passive Filters for Harmonic Mitigation

Abstract

The increasing penetration of nonlinear industrial loads significantly intensifies harmonic distortion in power systems, resulting in degraded power quality, increased power losses, and overheating in electrical equipment, as well as non-compliance with IEEE 519 standards. This study proposes a Jellyfish Search Algorithm (JSA)-based optimization framework for parameter tuning of C-Type passive filters in a medium-voltage industrial distribution system. The novelty of this work lies in the integration of a metaheuristic optimization approach with multi-harmonic constrained filter design to enhance attenuation performance beyond conventional analytical methods. Initial harmonic assessment reveals severe distortion levels, with total harmonic distortion (THD) reaching 23.55%, 18.67%, and 24.72% across phases L1–L3. A baseline analytical design employing dual C-Type filters tuned to the 3rd and 5th harmonics reduces THD to approximately 3.2%, meeting standard limits but still dominated by low-order harmonic components. To address this limitation, JSA is applied to optimally determine filter parameters by minimizing THD while preserving impedance characteristics at targeted harmonic frequencies. The optimized configuration further reduces THD to 1.99%, 1.66%, and 1.63% for phases L1–L3, respectively, without introducing adverse resonance effects within the studied frequency range. Convergence analysis indicates stable optimization behavior with a well-balanced exploration–exploitation mechanism. These results demonstrate that the proposed JSA-based approach provides a systematic and effective strategy for enhancing harmonic mitigation performance and advancing passive filter design in industrial power systems.