Multi-Objective Teaching–Learning-Based Optimization with Pareto Front for Optimal Design of Passive Power Filters

This paper proposes an optimal design method to suppress critical harmonics and improve the power factor by using passive filters (PPFs). The main objectives include (1) minimizing total harmonic distortion of voltage current, (2) initial investment cost, (3) maximizing fundamental reactive compensation. A methodology based on teaching–learning-based optimization (TLBO) Pareto optimality is proposed used solve this multi-objective PPF problem. integrated with both external archive fuzzy decision making. sub-group search strategy teacher selection are diversity non-dominated solutions (NDSs). In addition, a mechanism for topology combinations PPFs proposed. series case studies also conducted demonstrate performance effectiveness method. With mechanisms parameters PPFs, best compromise solution complete achieved.