Volume 16, Issue 3 (September 2020)                   IJEEE 2020, 16(3): 336-352 | Back to browse issues page


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Hosseinpour M, Sadeh J. Optimal Multiple FCLs Allocation Considering DG Penetration in Meshed Network With Multi-Level Voltages. IJEEE 2020; 16 (3) :336-352
URL: http://ijeee.iust.ac.ir/article-1-1484-en.html
Abstract:   (2475 Views)
Increasing the short circuit current due to the penetration of distributed generations (DGs) in various voltage levels and meshed topology is a basic problem in power systems. Using fault current limiter (FCL) is an efficient approach to mitigate the exceeded short circuit levels. In this paper, a new approach is presented for multiple FCLs locating to decrease short circuit levels in meshed networks with several subsystems and multi-level voltages. Modified hybrid genetic algorithm (GA) and sensitivity analysis (SA) are used to determine the type, number, location, and voltage level of FCLs. Also, an effective sensitivity index is proposed, which can reduce the search space for optimal allocation. This method suggests the optimal allocation with the least investment cost in multi-level voltages networks according to the FCL costs. The proposed method is evaluated in the IEEE 30-bus, 57-bus, and 300-bus test systems. Numerical results indicate the accuracy and efficiency of the proposed method.
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  • A novel iterative method to locate the FCLs optimally in multi-level voltages and meshed networks considering DG penetration.
  • A modified genetic algorithm and sensitivity analysis is used to determine the best allocation scenario based on the least economic costs and fault current reduction as technical constraints.
  • A new efficient sensitivity index is defined to reduce the search space of GA and calculation burden purposefully.
  • A framework has been proposed based on the analysis of the different behavior of the types of FCLs in fault current mitigation.

Type of Study: Research Paper |
Received: 2019/04/29 | Revised: 2019/07/30 | Accepted: 2019/08/03

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.