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<p>Any failure in the distribution network, a crucial component of a power system, must be swiftly recognized by relays. The presence of distributed generation resources in the distribution network poses a new challenge for the correct performance of overcurrent relays. These sources, by injecting fault current and changing the network structure, can lead to the maloperation of overcurrent relays and alter their performance. Overcurrent relays adhere to various standards, each with a specific characteristic curve. The aim of this paper is to optimize the coordination of overcurrent relay and its characteristic curve, in addition to refining other relay settings. This is achieved with the goal of reducing the operation times of both main and supporting relays and eliminating the inconsistencies between them. To address this issue, we employ a combination of genetic and differential optimization algorithms. The effectiveness of this method is proven through the implementation of different scenarios, demonstrating a reduction in the operation time of the relays.</p>

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Optimal synchronization of overcurrent relays in active distribution networks using a hybrid genetic-differential optimization algorithm

  • 期刊论文

  • 发表日期：

    2025年1月15日

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  • Ahad Jahandideh Shendi,
  • Leila Mohammadian,
  • Reza Ghanizadeh,
  • Jaber Pouladi,
  • Jamal Beiza

摘要

Any failure in the distribution network, a crucial component of a power system, must be swiftly recognized by relays. The presence of distributed generation resources in the distribution network poses a new challenge for the correct performance of overcurrent relays. These sources, by injecting fault current and changing the network structure, can lead to the maloperation of overcurrent relays and alter their performance. Overcurrent relays adhere to various standards, each with a specific characteristic curve. The aim of this paper is to optimize the coordination of overcurrent relay and its characteristic curve, in addition to refining other relay settings. This is achieved with the goal of reducing the operation times of both main and supporting relays and eliminating the inconsistencies between them. To address this issue, we employ a combination of genetic and differential optimization algorithms. The effectiveness of this method is proven through the implementation of different scenarios, demonstrating a reduction in the operation time of the relays.