TY - EJOUR
AU - Gupta, Sandeep
AU - Singh, Navdeep
AU - Joshi, Kirti
PY - 2024
DA - February
TI - Biogeography based Novel AI Optimization with SSSC for Optimal Power Flow
T2 - Majlesi Journal of Electrical Engineering
VL - 12
L1 - https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/biogeography-based-novel-ai-optimization-with-sssc-for-optimal-power-flow/
N2 - 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 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 appears to be 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 show that the proposed technique execution properly and can effectively apply 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. 
IS - 2
PB - OICC Press
KW - Optimal Power Flow (OPF), SSSC Device, FACTS Device and Optimization Technique, OpenCV, BBO 
EN -