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Charging demand based on the interaction among electric vehicles and renewable energy sources using hybrid technique

机译：Charging demand based on the interaction among electric vehicles and renewable energy sources using hybrid technique

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Abstract In this manuscript, an efficient hybrid technique is proposed for optimal allocation of electric vehicle charging spots in distribution network system. The proposed technique is the combination of Forensic Investigation Algorithm (FBI) and the Archimedean Optimization Algorithm (AOA), hence it is commonly known as FBIAOA technique. The main purpose of the proposed technique is “to decrease the real and reactive power loss through the optimal allocation of the electric vehicles parking lot, and also decreases the cost.” The proposed technique is used to evaluate the reliability of the smart grid based on the state matrix incorporation of random parameters of the electric vehicle. In addition, the proposed technique helps to increase the calculation speed by detecting the desired count of electric vehicle states required. The proposed technique is executed in MATLAB/Simulink platform. The efficiency of the proposed technique is compared with other existing techniques, like CHA, SSA and S2NA-GEO. The experimental results show that the proposed method significantly reduces the cost and also locates the optimal global solution efficiently and accurately.Graphical abstract

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