Volume 14, Issue 3 (September 2018)                   IJEEE 2018, 14(3): 289-298 | Back to browse issues page

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Hoshyarzadeh A S, Zaker B, Khodadoost Arani A A, Gharehpetian G B. Optimal DG Allocation and Thyristor-FCL Controlled Impedance Sizing for Smart Distribution Systems Using Genetic Algorithm. IJEEE 2018; 14 (3) :289-298
URL: http://ijeee.iust.ac.ir/article-1-1113-en.html
Optimal DG Allocation and Thyristor-FCL Controlled Impedance Sizing for Smart Distribution Systems Using Genetic Algorithm
A. S. Hoshyarzadeh , B. Zaker , A. A. Khodadoost Arani , G. B. Gharehpetian
Abstract:   (4289 Views)
Recently, smart grids have been considered as one of the vital elements in upgrading current power systems to a system with more reliability and efficiency. Distributed generation is necessary for most of these new networks. Indeed, in all cases that DGs are used in distribution systems, protection coordination failures may occur in multiple configurations of smart grids using DGs. In different configurations, there are various fault currents that can lead to protection failure. In this study, an optimal DG locating and Thyristor-Controlled Impedance (TCI) sizing of resistive, inductive, and capacitive type is proposed for distribution systems to prevent considerable changes in fault currents due to different modes of the smart grid. This problem is nonlinear constrained programming (NLP) and the genetic algorithm is utilized for the optimization. This optimization is applied to the IEEE 33-bus and IEEE 69-bus standard distribution systems. Optimum DG location and TCI sizing has carried out in steady fault currents in the grid-connected mode of these practical networks. Simulation results verify that the proposed method is effective for minimizing the protection coordination failure in such distribution networks.
Keywords: Distributed Generation , Genetic Algorithm , Protection Coordination , Smart Grid
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Type of Study: Research Paper | Subject: Power Quality
Received: 2017/06/27 | Revised: 2018/10/19 | Accepted: 2018/02/02
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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.