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Hybrid optimal online-overnight charging coordination of plug-in electric vehicles in smart grid

机译:智能电网中插电式电动汽车的混合最优在线-夜间充电协调

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Optimal coordinated charging of plugged-in electric vehicles (PEVs) in smart grid (SG) can be beneficial for both consumers and utilities. This paper proposes a hybrid optimal online followed by overnight charging coordination of high and low priority PEVs using discrete particle swarm optimization (DPSO) that considers the benefits of both consumers and electric utilities. Objective functions are online minimization of total cost (associated with grid losses and energy generation) and overnight valley filling through minimization of the total load levels. The constraints include substation transformer loading, node voltage regulations and the requested final battery state of charge levels (SOCreq). The main challenge is optimal selection of the overnight starting time (t(optimal-ovemight,start)) to guarantee charging of all vehicle batteries to the SOCreq levels before the requested plug-out times (t(req)) which is done by simultaneously solving the online and overnight objective functions. The online-overnight PEV coordination approach is implemented on a 449-node SG; results are compared for uncoordinated and coordinated battery charging as well as a modified strategy using cost minimizations for both online and overnight coordination. The impact of t(optimal-overnightstart) on performance of the proposed PEV coordination is investigated. Crown Copyright (C) 2016 Published by Elsevier B.V. All rights reserved.
机译:智能电网(SG)中插电式电动车(PEV)的最佳协调充电方式对消费者和公用事业均有利。本文提出了一种混合最优在线方法,其后使用离散粒子群优化(DPSO)对高优先级和低优先级PEV进行夜间充电协调,同时考虑了消费者和电力公司的利益。目标功能是在线使总成本最小化(与电网损失和能源产生有关),并通过使总负荷水平最小化来实现夜间填谷。约束条件包括变电站变压器负载,节点电压调节和要求的最终电池充电状态(SOCreq)。主要挑战是优化隔夜启动时间(t(optical-ovemight,start)),以确保在要求的插入时间(t(req))之前将所有车辆电池充电至SOCreq水平,这是同时完成的解决在线和通宵目标功能。在线过夜PEV协调方法是在449个节点的SG上实现的;比较了不协调和协调的电池充电的结果,以及使用成本最小化进行在线和通宵协调的修改策略。研究了t(最优过夜开始时间)对建议的PEV协调性能的影响。官方版权(C)2016,由Elsevier B.V.保留所有权利。

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