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On the aggregate grid load imposed by battery health-conscious charging of plug-in hybrid electric vehicles

机译:插电式混合动力汽车的电池健康意识充电对电网总负荷的影响

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摘要

This article examines the problem of estimating the aggregate load imposed on the power grid by the battery health-conscious charging of plug-in hybrid electric vehicles (PHEVs). The article begins by generating a set of representative daily trips using (i) the National Household Travel Survey (NHTS) and (ii) a Markov chain model of both federal and naturalistic drive cycles. A multi-objective optimizer then uses each of these trips, together with PHEV powertrain and battery degradation models, to optimize both PHEV daily energy cost and battery degradation. The optimizer achieves this by varying (i) the amounts of charge obtained from the grid by each PHEV, and (ii) the timing of this charging. The article finally computes aggregate PHEV power demand by accumulating the charge patterns optimized for individual PHEV trips. The results of this aggregation process show a peak PHEV load in the early morning (between 5.00 and 6.00 a.m.), with approximately half of all PHEVs charging simultaneously. The ability to charge at work introduces smaller additional peaks in the aggregate load pattern. The article concludes by exploring the sensitivity of these results to the relative weighting of the two optimization objectives (energy cost and battery health), battery size, and electricity price.
机译:本文研究了估算插电式混合动力汽车(PHEV)的电池健康意识充电对电网造成的总负载的问题。本文首先使用(i)国家家庭出行调查(NHTS)和(ii)联邦和自然驾驶周期的马尔可夫链模型生成一组有代表性的日常出行。然后,多目标优化器将这些行程中的每一个与PHEV动力总成和电池退化模型一起使用,以优化PHEV的每日能源成本和电池退化。优化器通过改变(i)每个PHEV从电网获得的电荷量,以及(ii)充电时间来实现这一点。文章最后通过累积针对各个PHEV行程优化的充电模式,计算了总的PHEV功率需求。此汇总过程的结果显示,在清晨(凌晨5.00至6.00之间),PHEV达到峰值,所有PHEV的大约一半同时充电。工作时的充电能力会在总负载模式中引入较小的附加峰值。本文通过探讨这些结果对两个优化目标(能源成本和电池运行状况),电池尺寸和电价的相对权重的敏感性得出结论。

著录项

  • 来源
    《Journal of power sources》 |2011年第20期|p.8747-8754|共8页
  • 作者单位

    Control Optimization Laboratory, Mechanical and Nuclear Engineering Department. The Pennsylvania State University. United States;

    Automated Modeling Laboratory, Department of Mechanical Engineering, University of Michigan, Ann Arbor, United States;

    Control Optimization Laboratory, Mechanical and Nuclear Engineering Department. The Pennsylvania State University. United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    plug-in hybrid electric vehicles; grid load modeling; lithium-ion battery degradation;

    机译:插电式混合动力汽车;网格负荷建模;锂离子电池退化;

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