A otimização de filtros passivos de harmônicos em sistemas elétricos industriais

Abstract

This article presents an analysis of the evolution of optimization formulations for passive harmonic filters in industrial power systems, highlighting the transition from single-objective to multi-objective formulations. Optimization methods such as Sequential Quadratic Programming (SQP), Simulated Annealing (SA), Differential Evolution (DE), Artificial Neural Networks (ANN), Particle Swarm Optimization (PSO), and Genetic Algorithms (GA), among others, are discussed. The work shows how formulations have evolved to better represent the complexity of the problem, considering more comprehensive objective functions and constraints.