Intelligent Control of an Active Front-End Converter: Deep Reinforcement Learning Approach

Oswaldo Menendez, Diana Lopez-Caiza, Alvaro Prado, Freddy Flores-Bahamonde, José Rodríguez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Deep reinforcement learning-based algorithms exhibit significant potential in developing robust model-free control systems for the next power converter generation. This work presents a control strategy based on a deep reinforcement learning (DRL) framework to operate an Active Front-End (AFE). The research's originality lies in finding an optimal control policy that leverages DRL's capabilities to enhance the AFE control performance, all without prior information regarding power converter dynamics and parameters. Moreover, the control strategy is designed to ensure the adaptability of the converter across diverse operational scenarios. To this end, multiple intelligent agents are developed, trained, tested, and validated using the AFE converter dynamics. Simulated results demonstrated that the proposed control methodology exhibits robustness, effectively handling uncertainties associated with the converter. Also, the empirical findings reveal that the proposed control strategy presents a solid performance in the current control and DC-link voltage control tasks, with a maximum Total Harmonic Distortion of 4.25% for 10 kHz sampling frequency.

Original languageEnglish
Title of host publicationCOBEP 2023 - 17th Brazilian Power Electronics Conference and SPEC 2023 - 8th IEEE Southern Power Electronics Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350321128
DOIs
Publication statusPublished - 2023
Event8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023 - Florianopolis, Brazil
Duration: 26 Nov 202329 Nov 2023

Publication series

NameCOBEP 2023 - 17th Brazilian Power Electronics Conference and SPEC 2023 - 8th IEEE Southern Power Electronics Conference, Proceedings

Conference

Conference8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023
Country/TerritoryBrazil
CityFlorianopolis
Period26/11/2329/11/23

Keywords

  • Active Front-End
  • Deep reinforcement learning
  • machine learning
  • neural networks

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization

Fingerprint

Dive into the research topics of 'Intelligent Control of an Active Front-End Converter: Deep Reinforcement Learning Approach'. Together they form a unique fingerprint.

Cite this