Citation
Zhongjing Ma, Suli Zou, Long Ran, Xingyu Shi, Ian Hiskens. "Efficient decentralized coordination of large-scale plug-in electric vehicle charging". Automatica, 69:35-47, 2016.

Abstract
Minimizing the grid impacts of large-scale plug-in electric vehicle (PEV) charging tends to be associated with coordination strategies that seek to fill the overnight valley in electricity demand. However such strategies can result in high charging power, raising the possibility of local overloads within the distribution grid and of accelerated battery degradation. The paper establishes a framework for PEV charging coordination that facilitates the tradeoff between total generation cost and the local costs associated with overloading and battery degradation. A decentralized approach to solving the resulting large-scale optimization problem involves each PEV minimizing their charging cost with respect to a forecast price profile while taking into account local grid and battery effects. The charging strategies proposed by participating PEVs are used to update the price profile which is subsequently rebroadcast to the PEVs. The process then repeats. It is shown that under mild conditions this iterative process converges to the unique, efficient (socially optimal) coordination strategy.

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  Zhongjing Ma, Suli Zou, Long Ran, Xingyu Shi, Ian Hiskens.
  <a
  href="http://www.cps-forces.org/pubs/223.html"
  >Efficient decentralized coordination of large-scale
  plug-in electric vehicle charging</a>,
  <i>Automatica</i>, 69:35-47,  2016.

• Plain text

  Zhongjing Ma, Suli Zou, Long Ran, Xingyu Shi, Ian Hiskens.
  "Efficient decentralized coordination of large-scale
  plug-in electric vehicle charging".
  <i>Automatica</i>, 69:35-47,  2016.

• BibTeX

  @article{MaZouRanShiHiskens16_EfficientDecentralizedCoordinationOfLargescalePlugin,
      author = {Zhongjing Ma and Suli Zou and Long Ran and Xingyu
                Shi and Ian Hiskens},
      title = {Efficient decentralized coordination of
                large-scale plug-in electric vehicle charging},
      journal = {Automatica},
      volume = {69},
      pages = {35-47},
      year = {2016},
      abstract = {Minimizing the grid impacts of large-scale plug-in
                electric vehicle (PEV) charging tends to be
                associated with coordination strategies that seek
                to fill the overnight valley in electricity
                demand. However such strategies can result in high
                charging power, raising the possibility of local
                overloads within the distribution grid and of
                accelerated battery degradation. The paper
                establishes a framework for PEV charging
                coordination that facilitates the tradeoff between
                total generation cost and the local costs
                associated with overloading and battery
                degradation. A decentralized approach to solving
                the resulting large-scale optimization problem
                involves each PEV minimizing their charging cost
                with respect to a forecast price profile while
                taking into account local grid and battery
                effects. The charging strategies proposed by
                participating PEVs are used to update the price
                profile which is subsequently rebroadcast to the
                PEVs. The process then repeats. It is shown that
                under mild conditions this iterative process
                converges to the unique, efficient (socially
                optimal) coordination strategy.},
      URL = {http://cps-forces.org/pubs/223.html}
  }
  

Posted by Ian Hiskens on 28 Feb 2017.
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