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Distribution Network Reconfiguration for Power Loss Reduction and Voltage Profile Improvement Using Chaotic Stochastic Fractal Search Algorithm

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  • Tung Tran The
  • Dieu Vo Ngoc
  • Nguyen Tran Anh

Abstract

This paper proposes a chaotic stochastic fractal search algorithm (CSFSA) method to solve the reconfiguration problem for minimizing the power loss and improving the voltage profile in distribution systems. The proposed method is a metaheuristic method developed for overcoming the weaknesses of the conventional SFSA with two processes of diffuse and update. In the first process, new points will be created from the initial points by the Gaussian walk. For the second one, SFSA will update better positions for the particles obtained in the diffusion process. In addition, this study has also integrated the chaos theory to improve the SFSA diffusion process as well as increase the rate of convergence and the ability to find the optimal solution. The effectiveness of the proposed CSFSA has been verified on the 33-bus, 84-bus, 119-bus, and 136-bus distribution systems. The obtained results from the test cases by CSFSA have been verified to those from other natural methods in the literature. The result comparison has indicated that the proposed method is more effective than many other methods for the test systems in terms of power loss reduction and voltage profile improvement. Therefore, the proposed CSFSA can be a very promising potential method for solving the reconfiguration problem in distribution systems.

Suggested Citation

  • Tung Tran The & Dieu Vo Ngoc & Nguyen Tran Anh, 2020. "Distribution Network Reconfiguration for Power Loss Reduction and Voltage Profile Improvement Using Chaotic Stochastic Fractal Search Algorithm," Complexity, Hindawi, vol. 2020, pages 1-15, March.
    • Handle: RePEc:hin:complx:2353901
    DOI: 10.1155/2020/2353901
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    Cited by:

    1. Mohamed Abd-El-Hakeem Mohamed & Ziad M. Ali & Mahrous Ahmed & Saad F. Al-Gahtani, 2021. "Energy Saving Maximization of Balanced and Unbalanced Distribution Power Systems via Network Reconfiguration and Optimum Capacitor Allocation Using a Hybrid Metaheuristic Algorithm," Energies, MDPI, vol. 14(11), pages 1-24, May.
    2. O. D. Montoya & W. Gil-González & J. C. Hernández & D. A. Giral-Ramírez & A. Medina-Quesada, 2020. "A Mixed-Integer Nonlinear Programming Model for Optimal Reconfiguration of DC Distribution Feeders," Energies, MDPI, vol. 13(17), pages 1-22, August.
    3. Ayşe Aybike Şeker & Tuba Gözel & Mehmet Hakan Hocaoğlu, 2021. "BIBC Matrix Modification for Network Topology Changes: Reconfiguration Problem Implementation," Energies, MDPI, vol. 14(10), pages 1-16, May.

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