Optimal Sizing and Sitting of Distributed Genetation for Power System using Bacterial Foraging Algorithm
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064



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Research Paper | Electrical Engineering | Iran | Volume 3 Issue 11, November 2014

Optimal Sizing and Sitting of Distributed Genetation for Power System using Bacterial Foraging Algorithm

Mahdi Jabbari

Distributed generation (DG) is the use of small generation sets connected to the grid or feeding power Islands based on technologies such as internal combustion engines, small and micro turbines, full cell, photo voltaic and wind plants. Driven by increasing environmental concerns and increasing amount of new generation technologies, it is expected that many new generation technologies, including renewable generation, will be connected to electrical power system in the near future, therefore, optimal sitting and sizing conditions shall be studied to improve overall power system operation. In this paper, improvement of voltage profile, improvement of voltage stability and less reduction is investigated. Bacterial foraging algorithm is directly utilized to study about nonlinear problems of sizing and sitting of distributed generation. Also, it is optimized using of Bacterial foraging algorithm and the simulation results is compared with genetic algorithm and particle swarm optimization. The 33-bus test system is employed in the study with dynamic load conditions. An Analysis on the potential impacts that DG might have on the stability and quality of the test system is studied. A simulation program, MATLAB, is used for this purpose, which executes dynamic calculations on the system

Keywords: BFA algorithm, loss, indicator

Edition: Volume 3 Issue 11, November 2014

Pages: 140 - 143

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How to Cite this Article?

Mahdi Jabbari, "Optimal Sizing and Sitting of Distributed Genetation for Power System using Bacterial Foraging Algorithm", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=20101406, Volume 3 Issue 11, November 2014, 140 - 143

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