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Information Journal Paper

Title

BIOGEOGRAPHY BASED NOVEL AI OPTIMIZATION WITH SSSC FOR OPTIMAL POWER FLOW

Pages

  39-45

Keywords

BBO 
OPTIMAL POWER FLOW (OPF) 

Abstract

 This paper objective presents static synchronous series compensation FACTS DEVICE with biogeography based optimization (BBO) to deal for obtaining worthwhile power flow control. The biogeography based optimization method is utilized to find the optimal fitted child sets by surviving parents with the help of migration and mutation Jaipur process. The present BBO technique from the evolutionary strategy with static synchronous series compensator provides improved outcomes in comparison to other optimization methods. The simulation outcomes illustrate that the proposed BBO algorithm is efficacious, secure and correct to search the optimized values with SSSC based FACTS DEVICEs. The proposed method is considering the solution quality an optimistic substitute method for extricating the OPF problems. The simplification and effectiveness of this method are validated on the IEEE 57 bus and 75 bus Systems. In this paper, from the outcome results, it is clearly shown that the proposed technique execution can be properly and effectively applied to the optimal position of multiple OPF problems. i.e. BBO based algorithm with SSSC FACTS DEVICE is found better results when compared to without SSSC DEVICE in all aspects.

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    • Cite

    APA: Copy

    GUPTA, SANDEEP, SINGH, NAVDEEP, & JOSHI, KIRTI. (2018). BIOGEOGRAPHY BASED NOVEL AI OPTIMIZATION WITH SSSC FOR OPTIMAL POWER FLOW. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, 12(2), 39-45. SID. https://sid.ir/paper/715972/en

    Vancouver: Copy

    GUPTA SANDEEP, SINGH NAVDEEP, JOSHI KIRTI. BIOGEOGRAPHY BASED NOVEL AI OPTIMIZATION WITH SSSC FOR OPTIMAL POWER FLOW. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2018;12(2):39-45. Available from: https://sid.ir/paper/715972/en

    IEEE: Copy

    SANDEEP GUPTA, NAVDEEP SINGH, and KIRTI JOSHI, “BIOGEOGRAPHY BASED NOVEL AI OPTIMIZATION WITH SSSC FOR OPTIMAL POWER FLOW,” MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, vol. 12, no. 2, pp. 39–45, 2018, [Online]. Available: https://sid.ir/paper/715972/en

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