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Bacterial graphical user interface oriented by particle swarm optimization strategy for optimization of multiple type DFACTS for power quality enhancement in distribution system

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Abstract

This study proposes a graphical user interface (GUI) based on an enhanced bacterial foraging optimization (EBFO) to find the optimal locations and sizing parameters of multi-type DFACTS in large-scale distribution systems. The proposed GUI based toolbox, allows the user to choose between single and multiple DFACTS allocations, followed by the type and number of them to be allocated. The EBFO is then applied to obtain optimal locations and ratings of the single and multiple DFACTS. This is found to be faster and provides more accurate results compared to the usual PSO and BFO. Results obtained with MATLAB/Simulink simulations are compared with PSO, BFO and enhanced BFO. It reveals that enhanced BFO shows quick convergence to reach the desired solution there by yielding superior solution quality. Simulation results concluded that the EBFO based multiple DFACTS allocation using DSSSC, APC and DSTATCOM is preferable to reduce power losses, improve load balancing and enhance voltage deviation index to 70%, 38% and 132% respectively and also it can improve loading factor without additional power loss.

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Acknowledgments

This work was supported by Islamic Azad University, Borujerd Branch, Iran. The authors would like to acknowledge staffs of University.

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Authors and Affiliations

  1. Department of Electrical Engineering, Borujerd Branch, Islamic Azad University, Borujerd, Iran

    M. Mohammadi, M. Montazeri & S. Abasi

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  1. M. Mohammadi
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  2. M. Montazeri
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  3. S. Abasi
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Correspondence to M. Mohammadi.

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Foundation item: Project supported by Borujerd Branch, Islamic Azad University, Iran

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Mohammadi, M., Montazeri, M. & Abasi, S. Bacterial graphical user interface oriented by particle swarm optimization strategy for optimization of multiple type DFACTS for power quality enhancement in distribution system. J. Cent. South Univ. 24, 569–588 (2017). https://doi.org/10.1007/s11771-017-3459-z

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  • DOI: https://doi.org/10.1007/s11771-017-3459-z

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