Microgrids have been used to manage the electricity grid with a large number of integrated distributed generators. Without a proper control and management mechanism, the Microgrid efficiency and reliability may plummet which will influence the operation of critical loads connected to the grid. A Fuzzy-Droop controller is proposed to maintain the active and reactive power balance in the Microgrid and, hence, maintain frequency at the nominal value. A particle swarm optimization algorithm is implemented over the proposed design to locate the best gain values of the utilized controllers according to a certain cost function. The proposed control scheme is applied to the diesel generator and battery system units which will guarantee a rapid and sufficient response to disturbances in the network. Furthermore, a weak connection between the Microgrid and the main electricity grid is assumed, which will add more challenges to the proposed control technique. The effectiveness of the design is evaluated and compared to other control schemes. © 2022 IEEE.
Original languageEnglish
Title of host publication29th International Workshop on Electric Drives: Advances in Power Electronics for Electric Drives, IWED 2022, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-7
Number of pages7
Volume1 Vol
ISBN (Electronic)978-1-6654-6786-5
ISBN (Print)978-1-6654-6787-2
DOIs
Publication statusPublished - 2022
Event2022 29th International Workshop on Electric Drives: Advances in Power Electronics for Electric Drives (IWED) - Moscow, Russian Federation
Duration: 26 Jan 202229 Jan 2022

Publication series

NameInternational Workshop on Electric Drives: Advances in Power Electronics for Electric Drives, IWED, Proceedings

Conference

Conference2022 29th International Workshop on Electric Drives: Advances in Power Electronics for Electric Drives (IWED)
Period26/01/202229/01/2022

    ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

ID: 33987256