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Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation

Received: 21 June 2017    Accepted: 10 July 2017    Published: 11 August 2017
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Abstract

Reactive power dispatch plays a main role in order to provide good facility secure and economic operation in the power system. Optimal reactive power dispatch (ORPD) is a nonlinear optimization problem and has both equality and inequality constraints. ORPD is defined as the minimization of active power loss by controlling a number of variables. Due to complex characteristics of ORPD, heuristic optimization has become an efficient solver. In this paper, particle swarm optimization (PSO) algorithm and MATPOWER toolbox are applied to solve the ORPD problem for distribution system with distributed generating (DG) plant. The proposed method minimizes the active power loss in a practical power system as well as determines the optimal placement of a new installed DG. The practical 41-bus, 6-machine power distribution network of Myingyan area is used to evaluate the performance. The result shows that the adjustment of control variables of distribution power network with a new DG gives a better approach than adjustment only the control variables without DG.

Published in International Journal of Energy and Power Engineering (Volume 6, Issue 4)
DOI 10.11648/j.ijepe.20170604.12
Page(s) 53-60
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), 2024. Published by Science Publishing Group

Keywords

Active Power Loss Minimization, Control Variables, DG, ORPD, PSO

References
[1] W. Ongsakul and D. N. Vo, “Artificial Intelligence in Power System Optimization,” Taylor & Francis Group, LLC, 2013.
[2] L. Shengqi, Z. Lilin, L. Yongan, and H. Zhengping, “Optimal Reactive Power Planning of Radial Distribution Systems with Distributed Generation,” Third International Conference on Intelligent System Design and Engineering Applications, 2013. pp. 1030-1033.
[3] T. Sharma, A. Yadav, S. Jamhoria, and R. Chaturvedi, “Comparative Study of Methods for Optimal Reactive Power Dispatch,” Electrical and Electronics Engineering, vol. 3, no. 3, 2014, pp. 53-61.
[4] K. Naima, B. Fadela, C. Imene, and C. Abdelkader, “Use of Genetic Algorithm and Particle Swarm Optimization Methods for the Optimal Control of the Reactive Power in Western Algerian Power System,” Energy Procedia 74, 2015, pp. 265-272.
[5] Y. Amrane and M. Boudour, “Optimal Reactive Power Dispatch Based on Particle Swarm Optimization Approach Applied to the Algerian Electric Power System,” IEEE 2014 11th International Multi-Conference on Systems, Signals and Devices – Castelldefels-Barcelona, Spain, 2014.
[6] Kittavit Buayai, Kittiwut Chinnabutr, Prajuap Intarawong, and Kaan Kerdchuen, “Applied MATPOWER for Power System Optimization Research,” Energy Procedia, vol. 56, 2014, pp. 505-509.
[7] A. Ghasemi, and A. Tohidi, “Multi Objective Optimal Reactive Power Dispatch Using a New Multi Objective Strategy,” Electrical Power and Energy Systems, vol. 57, 2014, pp. 318-334.
[8] T. Malakar, and S. K. Goswami, “Active and Reactive Power Dispatch with minimum control movement,” Electrical Power System Research, vol. 44, 2013, pp. 77-87.
[9] Y. Li, Y. Wang, and B. Li, “A Hybrid Artificial Bee Colony assisted Differential Evolution Algorithm for Optimal Reactive Power Flow,” Electrical Power System Research, vol. 52, 2013, pp. 25-33.
[10] M. Zamri Che Wanik, I. Erlich, and A. Mohamed, “Intelligent Management of Distributed Generators Reactive Power for Loss Minimization and Voltage Control,” IEEE, 2010, pp. 685-690.
[11] U. Leeton, T. Ratniyomchai and T. Kulworawanichpong, “Optimal Reactive Power Flow with Distributed Generating Plants in Electric Power Distribution Systems,” International Conference on Advances in Energy Engineering, 2010.
[12] J. Zhu, R. D. Zimmerman and C. E. Murillo-Sanchez, “MATPOWER 5.1 User’s Manual,” March 20, 2015.
[13] N. K. Patel, and B. N. Suthar, “Optimal Reactive Power Dispatch Using Particle Swarm Optimization in Deregulated Environment,” International Conference on EESCO, 2015.
[14] S. Pandya, and R. Roy, “Particle Swarm Optimization Based Optimal Reactive Power Dispatch,” IEEE International Conference on Electrical Computer and Communication Technologies-Coimbatore, India, 2015.
Cite This Article
  • APA Style

    Khine Zin Oo, Kyaw Myo Lin, Tin Nilar Aung. (2017). Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation. International Journal of Energy and Power Engineering, 6(4), 53-60. https://doi.org/10.11648/j.ijepe.20170604.12

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    ACS Style

    Khine Zin Oo; Kyaw Myo Lin; Tin Nilar Aung. Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation. Int. J. Energy Power Eng. 2017, 6(4), 53-60. doi: 10.11648/j.ijepe.20170604.12

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    AMA Style

    Khine Zin Oo, Kyaw Myo Lin, Tin Nilar Aung. Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation. Int J Energy Power Eng. 2017;6(4):53-60. doi: 10.11648/j.ijepe.20170604.12

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  • @article{10.11648/j.ijepe.20170604.12,
      author = {Khine Zin Oo and Kyaw Myo Lin and Tin Nilar Aung},
      title = {Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation},
      journal = {International Journal of Energy and Power Engineering},
      volume = {6},
      number = {4},
      pages = {53-60},
      doi = {10.11648/j.ijepe.20170604.12},
      url = {https://doi.org/10.11648/j.ijepe.20170604.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20170604.12},
      abstract = {Reactive power dispatch plays a main role in order to provide good facility secure and economic operation in the power system. Optimal reactive power dispatch (ORPD) is a nonlinear optimization problem and has both equality and inequality constraints. ORPD is defined as the minimization of active power loss by controlling a number of variables. Due to complex characteristics of ORPD, heuristic optimization has become an efficient solver. In this paper, particle swarm optimization (PSO) algorithm and MATPOWER toolbox are applied to solve the ORPD problem for distribution system with distributed generating (DG) plant. The proposed method minimizes the active power loss in a practical power system as well as determines the optimal placement of a new installed DG. The practical 41-bus, 6-machine power distribution network of Myingyan area is used to evaluate the performance. The result shows that the adjustment of control variables of distribution power network with a new DG gives a better approach than adjustment only the control variables without DG.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Particle Swarm Optimization Based Optimal Reactive Power Dispatch for Power Distribution Network with Distributed Generation
    AU  - Khine Zin Oo
    AU  - Kyaw Myo Lin
    AU  - Tin Nilar Aung
    Y1  - 2017/08/11
    PY  - 2017
    N1  - https://doi.org/10.11648/j.ijepe.20170604.12
    DO  - 10.11648/j.ijepe.20170604.12
    T2  - International Journal of Energy and Power Engineering
    JF  - International Journal of Energy and Power Engineering
    JO  - International Journal of Energy and Power Engineering
    SP  - 53
    EP  - 60
    PB  - Science Publishing Group
    SN  - 2326-960X
    UR  - https://doi.org/10.11648/j.ijepe.20170604.12
    AB  - Reactive power dispatch plays a main role in order to provide good facility secure and economic operation in the power system. Optimal reactive power dispatch (ORPD) is a nonlinear optimization problem and has both equality and inequality constraints. ORPD is defined as the minimization of active power loss by controlling a number of variables. Due to complex characteristics of ORPD, heuristic optimization has become an efficient solver. In this paper, particle swarm optimization (PSO) algorithm and MATPOWER toolbox are applied to solve the ORPD problem for distribution system with distributed generating (DG) plant. The proposed method minimizes the active power loss in a practical power system as well as determines the optimal placement of a new installed DG. The practical 41-bus, 6-machine power distribution network of Myingyan area is used to evaluate the performance. The result shows that the adjustment of control variables of distribution power network with a new DG gives a better approach than adjustment only the control variables without DG.
    VL  - 6
    IS  - 4
    ER  - 

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Author Information
  • Power System Research Unit, Department of Electrical Power Engineering, Mandalay Technological University, Mandalay, Myanmar

  • Power System Research Unit, Department of Electrical Power Engineering, Mandalay Technological University, Mandalay, Myanmar

  • Power System Research Unit, Department of Electrical Power Engineering, Mandalay Technological University, Mandalay, Myanmar

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