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首页> 外文期刊>Industrial Informatics, IEEE Transactions on >Expected Cost Minimization of Smart Grids With Plug-In Hybrid Electric Vehicles Using Optimal Distribution Feeder Reconfiguration
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Expected Cost Minimization of Smart Grids With Plug-In Hybrid Electric Vehicles Using Optimal Distribution Feeder Reconfiguration

机译:使用最优分配馈线重构的插电式混合动力汽车将智能电网的预期成本降至最低

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摘要

Stochastic charging behavior of plug-in hybrid electric vehicles (PHEVs) under different charging strategies brings new challenges for distribution networks such as feeder overloading and loss increase. In this way, the augmented penetration of these vehicles mandates employing new operative tools to inspect their impacts on electrical grids. Therefore, this paper proposes a novel optimal stochastic reconfiguration methodology to moderate the charging effect of PHEVs by changing the topology of grid using some remote controlled switches. Uncertainties associated with network demand, energy price, and PHEV charging behavior in different charging frameworks are handled with Monte Carlo simulation and the proposed stochastic problem is solved with krill herd optimization algorithm. Numerical studies on Tai-power distribution system verify the efficacy of proposed reconfiguration to improve the system performance considering PHEV charging loads.
机译:插电式混合动力汽车(PHEV)在不同充电策略下的随机充电行为给配电网络带来了新的挑战,例如馈线过载和损耗增加。以此方式,这些车辆的增加的渗透性要求采用新的操作工具来检查其对电网的影响。因此,本文提出了一种新颖的最优随机重配置方法,以通过使用一些遥控开关改变电网的拓扑结构来缓和PHEV的充电效果。通过蒙特卡罗模拟处理与网络需求,能源价格和PHEV充电行为相关的不确定性,并通过蒙特卡洛模拟处理,并通过磷虾群优化算法解决所提出的随机问题。 Tai配电系统的数值研究证明了考虑PHEV充电负载的建议重新配置以提高系统性能的有效性。

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