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Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm

Received: 26 August 2016     Accepted: 13 September 2016     Published: 19 October 2016
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Abstract

In this paper a method for solving optimal distribution network reconfiguration and optimal placement distributed generation (DG) with the objective of reducing power losses and improving voltage profile with the least amount of time using a combination of various techniques is offered. In the proposed method, first, a meta-heuristic algorithm (MHA) is used to solve the problem of optimal DG placement. The search space for using this technique has been reduced to the optimal scale which is why this technique is accurate and quick. After solving optimal DG placement using the abovementioned technique, a binary particular swarm optimization algorithm (BPSO) is presented for solving the network reconfiguration. In fact, by reducing the search space, the speed of the technique for solving the problem is improved. The proposed technique has been implemented with different scenarios on IEEE 33- and 69-node test systems. The comparison of the results with those of other methods indicates the effectiveness of this technique.

Published in International Journal of Energy and Power Engineering (Volume 5, Issue 5)
DOI 10.11648/j.ijepe.20160505.11
Page(s) 163-170
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Distribution Network Reconfiguration, Distributed Generation, Hybrid Algorithm, Meta-Heuristic Algorithm, Binary Particular Swarm Optimization Algorithm, Power Loss

References
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Cite This Article
  • APA Style

    Mohammad Ali Hormozi, Mohammad Barghi Jahromi, Gholamreza Nasiri. (2016). Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm. International Journal of Energy and Power Engineering, 5(5), 163-170. https://doi.org/10.11648/j.ijepe.20160505.11

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    ACS Style

    Mohammad Ali Hormozi; Mohammad Barghi Jahromi; Gholamreza Nasiri. Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm. Int. J. Energy Power Eng. 2016, 5(5), 163-170. doi: 10.11648/j.ijepe.20160505.11

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    AMA Style

    Mohammad Ali Hormozi, Mohammad Barghi Jahromi, Gholamreza Nasiri. Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm. Int J Energy Power Eng. 2016;5(5):163-170. doi: 10.11648/j.ijepe.20160505.11

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  • @article{10.11648/j.ijepe.20160505.11,
      author = {Mohammad Ali Hormozi and Mohammad Barghi Jahromi and Gholamreza Nasiri},
      title = {Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm},
      journal = {International Journal of Energy and Power Engineering},
      volume = {5},
      number = {5},
      pages = {163-170},
      doi = {10.11648/j.ijepe.20160505.11},
      url = {https://doi.org/10.11648/j.ijepe.20160505.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20160505.11},
      abstract = {In this paper a method for solving optimal distribution network reconfiguration and optimal placement distributed generation (DG) with the objective of reducing power losses and improving voltage profile with the least amount of time using a combination of various techniques is offered. In the proposed method, first, a meta-heuristic algorithm (MHA) is used to solve the problem of optimal DG placement. The search space for using this technique has been reduced to the optimal scale which is why this technique is accurate and quick. After solving optimal DG placement using the abovementioned technique, a binary particular swarm optimization algorithm (BPSO) is presented for solving the network reconfiguration. In fact, by reducing the search space, the speed of the technique for solving the problem is improved. The proposed technique has been implemented with different scenarios on IEEE 33- and 69-node test systems. The comparison of the results with those of other methods indicates the effectiveness of this technique.},
     year = {2016}
    }
    

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    T1  - Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm
    AU  - Mohammad Ali Hormozi
    AU  - Mohammad Barghi Jahromi
    AU  - Gholamreza Nasiri
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    DO  - 10.11648/j.ijepe.20160505.11
    T2  - International Journal of Energy and Power Engineering
    JF  - International Journal of Energy and Power Engineering
    JO  - International Journal of Energy and Power Engineering
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    PB  - Science Publishing Group
    SN  - 2326-960X
    UR  - https://doi.org/10.11648/j.ijepe.20160505.11
    AB  - In this paper a method for solving optimal distribution network reconfiguration and optimal placement distributed generation (DG) with the objective of reducing power losses and improving voltage profile with the least amount of time using a combination of various techniques is offered. In the proposed method, first, a meta-heuristic algorithm (MHA) is used to solve the problem of optimal DG placement. The search space for using this technique has been reduced to the optimal scale which is why this technique is accurate and quick. After solving optimal DG placement using the abovementioned technique, a binary particular swarm optimization algorithm (BPSO) is presented for solving the network reconfiguration. In fact, by reducing the search space, the speed of the technique for solving the problem is improved. The proposed technique has been implemented with different scenarios on IEEE 33- and 69-node test systems. The comparison of the results with those of other methods indicates the effectiveness of this technique.
    VL  - 5
    IS  - 5
    ER  - 

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Author Information
  • Fars Regional Electrical Company, Shiraz, Iran

  • Fars Regional Electrical Company, Shiraz, Iran

  • Fars Regional Electrical Company, Shiraz, Iran

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