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Electric vehicles (EVs) are set to revolutionize the transportation industry due to their benefits and incentives. Because of their onboard battery power, they have the distinct feature of being a distributed energy storage device. This function enables them to offer essential ancillary services such as load variance minimization on grid via vehicle-to-grid (V2G) operation. However, issues such as unsure EV availability and constantly evolving state of charge (SOC) preempted practical V2G implementation. By investigating the stochastic nature of EV grid connection, this article suggests a scheduling approach for V2G power exchange which tackles these obstacles. In this article, we propose a novel method for optimizing V2G power exchange scheduling using binary particle swarm optimization with Gravitational Search Algorithm. This hybrid optimization algorithm of BPSO and GSA has a faster convergence rate than either PSO or GSA alone, making it a much efficient method for optimizing V2G power exchange scheduling. As per statistical analysis of data, the proposed V2G scheduling approach might substantially flatter load profile. In order to concern the results and validate the recommended strategy, contrasts were made among the conductivity of suggested method's best-case situation and greatest performance of methods proposed in previous work on an associated subject.

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Optimal Scheduling of Vehicle-to-Grid Power Exchange Using Hybrid BPSO and GSA Approach

  • 会议论文

  • 发表日期：

    2025年

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  • Vikas Kumar Badhan,
  • Shelly Vadhera

摘要

Electric vehicles (EVs) are set to revolutionize the transportation industry due to their benefits and incentives. Because of their onboard battery power, they have the distinct feature of being a distributed energy storage device. This function enables them to offer essential ancillary services such as load variance minimization on grid via vehicle-to-grid (V2G) operation. However, issues such as unsure EV availability and constantly evolving state of charge (SOC) preempted practical V2G implementation. By investigating the stochastic nature of EV grid connection, this article suggests a scheduling approach for V2G power exchange which tackles these obstacles. In this article, we propose a novel method for optimizing V2G power exchange scheduling using binary particle swarm optimization with Gravitational Search Algorithm. This hybrid optimization algorithm of BPSO and GSA has a faster convergence rate than either PSO or GSA alone, making it a much efficient method for optimizing V2G power exchange scheduling. As per statistical analysis of data, the proposed V2G scheduling approach might substantially flatter load profile. In order to concern the results and validate the recommended strategy, contrasts were made among the conductivity of suggested method's best-case situation and greatest performance of methods proposed in previous work on an associated subject.