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Optimal Charging Scheduling of Electric Vehicles in Micro Grids Using Priority Algorithms and Particle Swarm Optimization

机译:基于优先级算法和粒子群算法的微电网电动汽车最优充电调度

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摘要

The large-scale integration of electric vehicles (EVs) into modern power grid brings both challenges and opportunities to the performance of the systems. This paper presents an optimal static (when EV is stationary) charging scheduling scheme of EVs to minimize the charging cost while complying with the constraints related to the status of the charging station. The proposed systematic charging scheme is based on "Particle Swarm Optimization (PSO)". It is compared with well-established algorithms such as "Arrival Time-Based priority (ATP) algorithm" and "SOC-Based Priority (SBP) algorithm". In addition, a microgrid scenario is further considered for reducing the consumption of energy from the grid and also, reducing the charging cost by properly shifting the EV load. Based on the study carried out for a sample test cases considered, it is found that the proposed scheme has better performance compared to the existing schemes.
机译:电动汽车(EV)大规模集成到现代电网中,给系统性能带来了挑战和机遇。本文提出了一种电动汽车的最佳静态(当电动汽车静止时)充电调度方案,以在满足与充电站状态相关的约束的同时,将充电成本降至最低。提出的系统计费方案基于“粒子群优化(PSO)”。将其与完善的算法进行比较,例如“基于到达时间的优先级(ATP)算法”和“基于SOC的优先级(SBP)算法”。此外,还考虑了微电网方案,以减少来自电网的能源消耗,并通过适当转移EV负载来降低充电成本。基于对考虑的样本测试案例进行的研究,发现与现有方案相比,该方案具有更好的性能。

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