Evidence map›Paper›PMID 39035509›Full record

ArticleHeliyon2024

Optimal hybrid resonant current controller for microgrids connected to an unbalanced IEEE test distribution network.

Gerardo Humberto Valencia-Rivera, Ivan Amaya, Jorge M Cruz-Duarte, José Carlos Ortiz-Bayliss, Guillermo Tapia-Tinoco, Juan Gabriel Avina-Cervantes

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Gerardo Humberto Valencia-RiveraSchool of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Monterrey 64849, Nuevo León, Mexico.
Ivan AmayaSchool of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Monterrey 64849, Nuevo León, Mexico.
Jorge M Cruz-DuarteSchool of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Monterrey 64849, Nuevo León, Mexico.
José Carlos Ortiz-BaylissSchool of Engineering and Sciences, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Monterrey 64849, Nuevo León, Mexico.
Guillermo Tapia-TinocoTelematics and Digital Signal Processing Research groups (CAs), Engineering Division, Campus Irapuato-Salamanca, University of Guanajuato, Carretera Salamanca-Valle de Santiago km 3.5 + 1.8 km, Comunidad de Palo Blanco, Salamanca 36885, Mexico.
Juan Gabriel Avina-CervantesTelematics and Digital Signal Processing Research groups (CAs), Engineering Division, Campus Irapuato-Salamanca, University of Guanajuato, Carretera Salamanca-Valle de Santiago km 3.5 + 1.8 km, Comunidad de Palo Blanco, Salamanca 36885, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microgrids (MGs) based on renewable energies have emerged as a proficient strategy for tackling power quality issues in conventional distribution networks. Nonetheless, MG systems require a suitable control scheme to supply energy optimally towards the electrical grid. This paper presents an innovative framework for designing hybrid Proportional-Resonant (PR) controllers with Linear Quadratic Regulators (LQR), PR+LQR, which merge relevant properties of PR and LQR controllers. This method simultaneously determines the MG control parameters and the current unbalanced factor generated at the distribution network. We select the traditional IEEE 13-bus test feeder network and place two MGs at strategic locations to validate our approach. Moreover, we use the Grey Wolf Optimizer (GWO) to find control parameters through a reliable fitness function that leads to high-performance microgrids. Finally, we conceive several tests to assess the efficacy of GWO for tuning the hybrid controller and compare the resulting data across distinct realistic operation conditions representing power quality events. So, we choose four case studies considering different renewable energy penetration indexes and power factors and evaluate the effects of the MGs over the distribution grid. We also compare the proposed hybrid PR+LQR controller against closely-related alternatives from the literature and validate its robustness and stability through the disk margin approach and the Nyquist criterion. Our numerical simulations prove that hybrid controllers driven by GWO are highly reliable strategies, yielding an average unbalanced current reduction of 30.03%.

Indexed as

49M3068T2093E3594C99Grey Wolf OptimizerIEEE test distribution networkMicrogridResonant controllerUnbalanced loads

Identifiers

PMID39035509
PMCPMC11259800

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.