Optimal passive LCL filter design for grid-connected converters in weak grids

In an era characterized by the increasing integration of renewable energy sources into the power grid, the stability and resilience of the grid have become paramount, especially in areas with weak grid infrastructure. One effective approach to mitigate the adverse effects of grid disturbances and harmonics is passive LCL (inductorcapacitor-inductor) filters. However, designing these filters for optimal performance under varying conditions remains challenging. This research paper presents an effective approach to addressing this challenge by utilizing the power of evolutionary algorithms, specifically Multi-Objective Particle Swarm Optimization (MOPSO) and Multi-Objective Genetic Algorithm (MOGA), to design optimal passive LCL filters for weak grid environments. The proposed method aims to enhance grid resilience by optimizing the filter parameters to consider a weak grid's unique characteristics and uncertainties. Minimizing the resonance frequency has succeeded in achieving power quality and stability improvements related to changes in grid impedance. The proposed approach achieves power quality and stability improvements related to changes in grid impedance and dealing with fragile conditions, which is the main scope of this paper. (c) 2017 Elsevier Inc. All rights reserved.