Optimal filter design for renewable energy system interconnection with the electrical grid: Increase of system’s frequency response characteristics and cost reduction

This work presents an intelligent design procedure for LLCL filters used to integrate voltage source inverters with the electrical grid based on a new variant of Jaya optimization algorithm. The developed filter design procedure focuses on improvement of the system’s frequency response characteristics. The decrease in the size of the filter inductors contributes to the resonance peak reduction and shifting it to higher frequencies. By shifting the first resonance peak from lower to higher frequencies, the system becomes more stable and easier to control. The developed design resulted in a reduction of t reduces 25%, 26.7%, and 26.4% of the inverter-side, grid-side, and capacitor brach inductors, respectively, compared to the literature method. In the four worst cases, all inductive elements of the resulting filters were smaller than those obtained using the conventional method, achieving up to 25%, 80%, and 51.6% reduction of the inverter-side, grid-side, and capacitor brach inductors, respectively. Furthermore, as a secondary outcome, there is a cost reduction on hardware, since there is a cutback on the size of all three LLCL filter inductors. • A novel variant of Jaya optimizer using multiple chaotic maps. • A new optimal design of LLCL filters. • The LLCL filter has a reduced cost due to the reduction of all inductive elements. • Improvement of the system’s frequency response characteristics.

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Publication Details

Journal
Franklin Open
Published
2026-03-12
DOI
https://doi.org/10.1016/j.fraope.2026.100565
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Optimal filter design for renewable energy system interconnection with the electrical grid: Increase of system’s frequency response characteristics and cost reduction

Tamiris Grossl bade, Paulo Jefferson Dias de Oliveira Evald, Mateus Santos Da Silva, Telles Brunelli Lazzarin et al.
Franklin Open
Microgrid Control and Optimization
article

Optimal filter design for renewable energy system interconnection with the electrical grid: Increase of system’s frequency response characteristics and cost reduction

Tamiris Grossl bade, Paulo Jefferson Dias de Oliveira Evald, Mateus Santos Da Silva, Telles Brunelli Lazzarin, Felipe Pontes de Matos
article en

Abstract

This work presents an intelligent design procedure for LLCL filters used to integrate voltage source inverters with the electrical grid based on a new variant of Jaya optimization algorithm. The developed filter design procedure focuses on improvement of the system’s frequency response characteristics. The decrease in the size of the filter inductors contributes to the resonance peak reduction and shifting it to higher frequencies. By shifting the first resonance peak from lower to higher frequencies, the system becomes more stable and easier to control. The developed design resulted in a reduction of t reduces 25%, 26.7%, and 26.4% of the inverter-side, grid-side, and capacitor brach inductors, respectively, compared to the literature method. In the four worst cases, all inductive elements of the resulting filters were smaller than those obtained using the conventional method, achieving up to 25%, 80%, and 51.6% reduction of the inverter-side, grid-side, and capacitor brach inductors, respectively. Furthermore, as a secondary outcome, there is a cost reduction on hardware, since there is a cutback on the size of all three LLCL filter inductors. • A novel variant of Jaya optimizer using multiple chaotic maps. • A new optimal design of LLCL filters. • The LLCL filter has a reduced cost due to the reduction of all inductive elements. • Improvement of the system’s frequency response characteristics.

Franklin OpenVol. 15
Universidade Federal de Pelotas (BR), Universidade Federal de Santa Catarina (BR), Instituto Federal de Educação, Ciência e Tecnologia de Santa Catarina (BR)
Affordable and clean energy
Openalex Percentile: Top 26%
Microgrid Control and Optimization
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