Optimal Allocation and Control of Superconducting Fault Current Limiter and ‎Superconducting Magnetic Energy Storage in Mesh Microgrid Networks to ‎Improve Fault Ride Through

Document Type : Research paper

Authors

Department of Electrical Engineering, Shahid Beheshti University, Evin, Tehran, Iran.‎

Abstract

Voltage drop during the fault can be effected on the performance of generation units such as wind turbines. The ability to ride through the fault is important for these generation units. Superconducting fault current limiter and superconducting magnetic energy storage can improve the fault ride through due to fault current limiting and voltage restoring ability during the fault, respectively. This paper presents a method for optimal allocation and control of superconducting magnetic energy storage and superconducting fault current limiters in meshed microgrids. For this purpose, the doubly-fed induction generator voltage deviation, the point of common coupling power deviation, the fault current of transmission lines, and superconducting fault current limiter and superconducting magnetic energy storage characteristics were considered as objective functions. In this paper, the optimization is performed in single-step and two-step by particle swarm optimization algorithm, and the system with the optimal superconducting magnetic energy storage and superconducting fault current limiters are analyzed and compared. The results of simulations show superconducting fault current limiter and superconducting magnetic energy storage reduce 85% of voltage drop, decreases 63% of doubly fed induction generator power deviation, and limits the maximum fault current of transmission lines by 9.8 pu. Finally, the status of the studied system variables has been investigated, in two scenarios related to the different fault locations with equipment that the optimal allocated.

Keywords

References

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Journal of Operation and Automation in Power Engineering
Volume 11, Issue 1
April 2023
Pages 22-32

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History

  • Receive Date: 22 September 2021
  • Revise Date: 17 January 2022
  • Accept Date: 18 January 2022

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