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Charge scheduling of a plug-in electric vehicle considering load demand uncertainty based on multi-stage stochastic optimization

机译:基于多阶段随机优化的考虑负荷需求不确定性的插电式电动汽车充电调度

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A plug-in electric vehicle (PEV) can be used for load shifting household demand using an optimal control strategy to minimize the overall cost of the owner. The PEV can provide initial charge, final desired charge and charging time data to the charging station when plugged in, and the information can be used in a decision-making model to charge/discharge the PEV storage unit in a cost effective manner. In this paper, a multi-stage stochastic optimization model is presented to improve on this decision-making process under demand uncertainty. In this framework, a coordinated control between PEV storage and household load is presented. The Stochastic Dual Dynamic Programming (SDDP) algorithm is applied to define the optimal charging/discharging profile for minimizing the household daily operation costs.
机译:插电式电动汽车(PEV)可使用最优控制策略来满足家庭需求的负荷转移,以最大程度地降低所有者的总体成本。当插入时,PEV可以向充电站提供初始充电,最终所需的充电和充电时间数据,并且该信息可以在决策模型中使用,以具有成本效益的方式对PEV存储单元进行充电/放电。本文提出了一种多阶段随机优化模型,以改进需求不确定性下的决策过程。在此框架中,提出了PEV储存和家庭负荷之间的协调控制。随机双重动态规划(SDDP)算法用于定义最佳充电/放电曲线,以最大程度地减少家庭的日常运营成本。

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