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A Distributed Cooperative Control for Islanded DC Microgrids Incorporating Time Delays

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

Abstract

This manuscript proposes a novel distributed cooperative control to optimize generation costs in DC microgrids, with consideration of time delays. Artstein's reduction method is employed to transform the time-delay system into an equivalent delay-free model. Building on this, a finite-time distributed control algorithm is introduced to minimize generation cost by aligning the incremental costs of distributed generation units (DGUs) within an accelerated convergence timeframe, while respecting both the capacity limits of DGUs and the transmission line losses. Additionally, a distributed control approach is developed to ensure finite-time voltage stability, balancing generation and consumption across the microgrid. A key feature of the proposed control approach is incorporating a prescribed performance function, ensuring that the system's transient and steady-state responses consistently meet the required performance criteria. This ensures enhanced reliability and operational effectiveness of the system. The superiority and robustness of the proposed strategy are demonstrated through extensive simulation case studies.

Original languageEnglish
Title of host publication2024 Saudi Arabia Smart Grid, SASG 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331576301
DOIs
StatePublished - 2024
Event2024 Saudi Arabia Smart Grid, SASG 2024 - Riyadh, Saudi Arabia
Duration: 16 Dec 202418 Dec 2024

Publication series

Name2024 Saudi Arabia Smart Grid, SASG 2024

Conference

Conference2024 Saudi Arabia Smart Grid, SASG 2024
Country/TerritorySaudi Arabia
CityRiyadh
Period16/12/2418/12/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • Artstein reduction
  • DC Microgrids
  • Finite-time controller
  • Optimal Operation
  • prescribed performance

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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