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Feeder Reconfiguration and Distributed Generator Placement in Electric Power Distribution Network

Received: 23 November 2018     Accepted: 13 December 2018     Published: 15 January 2019
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Abstract

Power system deregulation and shortage of transmission capacities have led to an increase interest in Distributed Generations (DGs) sources. The optimal location of DGs in power systems is very important for obtaining their maximum potential benefits. A novel approach is proposed in this paper for placement of Distributed Generation (DG) units in reconfigured distribution system with the aim of reduction of real power losses while satisfying operating constraints. This paper presents an efficient method for feeder reconfiguration associated with DG allocation in radial distribution networks for active power compensation by reduction in real power losses and enhancement in voltage profile. Modified plant growth simulation algorithm has been applied successfully to minimize real power loss because it does not require barrier factors or cross over rates because the objectives and constraints are dealt separately. The main advantage of this algorithm is continuous guiding search along with changing objective function because power from distributed generation is continuously varying so this can be applied for real time applications with required modifications. The proposed system has been implemented with different scenarios on 33 bus Yamethin distribution system.

Published in American Journal of Electrical and Computer Engineering (Volume 2, Issue 2)
DOI 10.11648/j.ajece.20180202.16
Page(s) 56-63
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), 2019. Published by Science Publishing Group

Keywords

Feeder Reconfiguration, DG, Sensitivity Analysis, Radial Distribution System, Location and Sizing

References
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  • APA Style

    Pyone Lai Swe. (2019). Feeder Reconfiguration and Distributed Generator Placement in Electric Power Distribution Network. American Journal of Electrical and Computer Engineering, 2(2), 56-63. https://doi.org/10.11648/j.ajece.20180202.16

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    ACS Style

    Pyone Lai Swe. Feeder Reconfiguration and Distributed Generator Placement in Electric Power Distribution Network. Am. J. Electr. Comput. Eng. 2019, 2(2), 56-63. doi: 10.11648/j.ajece.20180202.16

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    AMA Style

    Pyone Lai Swe. Feeder Reconfiguration and Distributed Generator Placement in Electric Power Distribution Network. Am J Electr Comput Eng. 2019;2(2):56-63. doi: 10.11648/j.ajece.20180202.16

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  • @article{10.11648/j.ajece.20180202.16,
      author = {Pyone Lai Swe},
      title = {Feeder Reconfiguration and Distributed Generator Placement in Electric Power Distribution Network},
      journal = {American Journal of Electrical and Computer Engineering},
      volume = {2},
      number = {2},
      pages = {56-63},
      doi = {10.11648/j.ajece.20180202.16},
      url = {https://doi.org/10.11648/j.ajece.20180202.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajece.20180202.16},
      abstract = {Power system deregulation and shortage of transmission capacities have led to an increase interest in Distributed Generations (DGs) sources. The optimal location of DGs in power systems is very important for obtaining their maximum potential benefits. A novel approach is proposed in this paper for placement of Distributed Generation (DG) units in reconfigured distribution system with the aim of reduction of real power losses while satisfying operating constraints. This paper presents an efficient method for feeder reconfiguration associated with DG allocation in radial distribution networks for active power compensation by reduction in real power losses and enhancement in voltage profile. Modified plant growth simulation algorithm has been applied successfully to minimize real power loss because it does not require barrier factors or cross over rates because the objectives and constraints are dealt separately. The main advantage of this algorithm is continuous guiding search along with changing objective function because power from distributed generation is continuously varying so this can be applied for real time applications with required modifications. The proposed system has been implemented with different scenarios on 33 bus Yamethin distribution system.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Feeder Reconfiguration and Distributed Generator Placement in Electric Power Distribution Network
    AU  - Pyone Lai Swe
    Y1  - 2019/01/15
    PY  - 2019
    N1  - https://doi.org/10.11648/j.ajece.20180202.16
    DO  - 10.11648/j.ajece.20180202.16
    T2  - American Journal of Electrical and Computer Engineering
    JF  - American Journal of Electrical and Computer Engineering
    JO  - American Journal of Electrical and Computer Engineering
    SP  - 56
    EP  - 63
    PB  - Science Publishing Group
    SN  - 2640-0502
    UR  - https://doi.org/10.11648/j.ajece.20180202.16
    AB  - Power system deregulation and shortage of transmission capacities have led to an increase interest in Distributed Generations (DGs) sources. The optimal location of DGs in power systems is very important for obtaining their maximum potential benefits. A novel approach is proposed in this paper for placement of Distributed Generation (DG) units in reconfigured distribution system with the aim of reduction of real power losses while satisfying operating constraints. This paper presents an efficient method for feeder reconfiguration associated with DG allocation in radial distribution networks for active power compensation by reduction in real power losses and enhancement in voltage profile. Modified plant growth simulation algorithm has been applied successfully to minimize real power loss because it does not require barrier factors or cross over rates because the objectives and constraints are dealt separately. The main advantage of this algorithm is continuous guiding search along with changing objective function because power from distributed generation is continuously varying so this can be applied for real time applications with required modifications. The proposed system has been implemented with different scenarios on 33 bus Yamethin distribution system.
    VL  - 2
    IS  - 2
    ER  - 

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Author Information
  • Department of Electrical Power Engineering, Technological University (Yamethin), Mandalay, Myanmar

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