• français
    • English
    français
  • Login
Help
View Item 
  •   Home
  • Laboratoire d'Electrotechnique et d'Electronique de Puissance (L2EP) de Lille
  • View Item
  • Home
  • Laboratoire d'Electrotechnique et d'Electronique de Puissance (L2EP) de Lille
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Convolutional Neural Network for the Classification of the Control Mode of Grid-Connected Power Converters

Article dans une revue avec comité de lecture
Author
OUALI, Rabah
410272 Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
ccLEGRY, Martin
405582 L2EP - Équipe Réseaux
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
DIEULOT, Jean-Yves
410272 Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
YIM, Pascal
410272 Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
ccGUILLAUD, Xavier
405582 L2EP - Équipe Réseaux
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
ccCOLAS, Frédéric
405582 L2EP - Équipe Réseaux
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]

URI
http://hdl.handle.net/10985/25982
DOI
10.3390/en17246458
Date
2024-12
Journal
ENERGIES

Abstract

With the integration of power converters into the power grid, it becomes crucial for the Transmission System Operator (TSO) to ascertain whether they are operating in Grid Forming or Grid Following modes. Due to intellectual properties, classification can only be performed based on non-intrusive measurements and models, such as admittance at the PCC. This classification poses a challenge as the TSO lacks precise knowledge of the actual control structures and algorithms. This paper introduces a novel classification algorithm based on Convolutional Neural Networks (CNN), capable of detecting patterns in sequential data. The proposed CNN utilizes a new architecture to separate admittances along the d and q axes, and a decision layer allows to determine the correct converter mode. The performance of the proposed CNN model was assessed through two tests and compared to the traditional feedforward model. The proposed CNN architecture demonstrates significant classification capabilities, as it is able to identify the control mode of the converter even when its control structure is not part of the training dataset.

Files in this item

Name:
L2EP_ENERGIES_2024_LEGRY.pdf
Size:
2.921Mb
Format:
PDF
Description:
main article
View/Open
CC BY
This document is available under CC BY license

Collections

  • Laboratoire d'Electrotechnique et d'Electronique de Puissance (L2EP) de Lille

Related items

Showing items related by title, author, creator and subject.

  • A Two-layer Model Predictive Control Based Secondary Control with Economic Performance Tracking for Islanded Microgrids 
    Communication avec acte
    LEGRY, Martin; COLAS, Frédéric; SAUDEMONT, Christophe; DIEULOT, Jean-Yves; DUCARME, Olivier (IEEE, 2018)
    This paper proposes a two-layer microgrid supervisor based on Model Predictive Control (MPC). The supervisor in the upper layer relies on an economical optimization that considers the cost of energy and the load and ...
  • Non-Linear Primary Control Mapping for Droop-Like Behavior of Microgrid Systems 
    Article dans une revue avec comité de lecture
    LEGRY, Martin; DIEULOT, Jean-Yves; COLAS, Frederic; SAUDEMONT, Christophe; DUCARME, Olivier (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    Interconnecting microgrids in LV power system presents appealing features such as self-healing or power quality. When networked microgrids are not connected to a strong utility grid, their Point of Common Coupling (PCC) ...
  • Mixed integer quadratic programming receding horizon microgrid supervisor 
    Communication avec acte
    LEGRY, Martin; COLAS, Frédéric; SAUDEMONT, Christophe; DIEULOT, Jean-Yves; DUCARME, Olivier (IEEE, 2019)
    This paper proposes to optimize the real time operation of a microgrid controlled with a two-layer Model Predictive Controller supervisor. Based on the classical decomposition of control level, the proposed supervisor ...
  • Coordinated control of active distribution networks to help a transmission system in emergency situation 
    Article dans une revue avec comité de lecture
    MORIN, J.; COLAS, Frédéric; DIEULOT, Jean-Yves; GRENARD, S.; GUILLAUD, Xavier (Springer, 2018)
    This paper addresses the relevance of using reactive power from Medium Voltage (MV) networks to support the voltages of a High Voltage (HV) rural network in real-time. The selection and analysis of different optimal ...
  • Confidence Level Optimization of DG Piecewise Affine Controllers in Distribution Grids 
    Article dans une revue avec comité de lecture
    BUIRE, Jerome; COLAS, Frédéric; DIEULOT, Jean-Yves; DE ALVARO, Leticia; GUILLAUD, Xavier (Institute of Electrical and Electronics Engineers, 2019)
    Distributed generators (DGs) reactive powers are controlled to mitigate voltage overshoots in distribution grids with stochastic power production and consumption. Classical DGs controllers may embed piecewise affine laws ...

Browse

All SAMCommunities & CollectionsAuthorsIssue DateCenter / InstitutionThis CollectionAuthorsIssue DateCenter / Institution

Newsletter

Latest newsletterPrevious newsletters

Statistics

Most Popular ItemsStatistics by CountryMost Popular Authors

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales