Abstract
Abstract
With the continuous promotion of electric vehicles (EVs), charging fees for EVs has gradually become a hot issue. Pointing at the defects of the bald eagle algorithm, such as slow rate of convergence and poor solving accuracy, the bald eagle search algorithm based on opposition learning and Gaussian variation (GBES) is proposed. The improved bald eagle algorithm has the characteristics of fast convergence speed and strong optimization ability. The model of EV charging cost minimum scheduling is optimized by the GBES, and its effectiveness is verified by simulation experiments.
Subject
Computer Science Applications,History,Education
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