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A scenario of vehicle-to-grid implementation and its double-layer optimal charging strategy for minimizing load variance within regional smart grids

机译:车辆到电网实施方案及其双层最佳充电策略,以最大程度地降低区域智能电网内的负载变化

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摘要

As an emerging new electrical load, plug-in electric vehicles (PEVs)' impact on the power grid has drawn increasing attention worldwide. An optimal scenario is that by digging the potential of PEVs as a move-able energy storage device, they may not harm the power grid by, for example, triggering extreme surges in demand at rush hours, conversely, the large-scale penetration of PEVs could benefit the grid through flattening the power load curve, hence, increase the stability, security and operating economy of the grid. This has become a hot issue which is known as vehicle-to-grid (V2G) technology within the framework of smart grid. In this paper, a scenario of V2G implementation within regional smart grids is discussed. Then, the problem is mathematically formulated. It is essentially an optimization problem, and the objective is to minimize the overall load variance. With the increase of the scale of PEVs and charging posts involved, the computational complexity will become tremendously high. Therefore, a double-layer optimal charging (DLOC) strategy is proposed to solve this problem. The comparative study demonstrates that the proposed DLOC algorithm can effectively solve the problem of tremendously high computational complexity arising from the large-scaled PEVs and charging posts involved.
机译:作为新兴的电力负荷,插电式电动汽车(PEV)对电网的影响已引起全球越来越多的关注。最佳方案是通过挖掘PEV作为可移动储能设备的潜力,它们可能不会对电网造成损害,例如,在高峰时段引发需求激增,反之则是PEV的大规模普及通过使电力负荷曲线变平可以使电网受益,从而增加电网的稳定性,安全性和运营经济性。这已经成为一个热门问题,在智能电网框架内被称为车对网(V2G)技术。本文讨论了在区域智能电网中实施V2G的情况。然后,对该问题进行数学表述。从本质上讲,这是一个优化问题,目标是最大程度地减少总负载变化。随着电动汽车和充电桩规模的增加,计算复杂度将变得非常高。因此,提出了双层最优充电(DLOC)策略来解决该问题。比较研究表明,提出的DLOC算法可以有效地解决大规模PEV和充电桩所引起的计算复杂性极高的问题。

著录项

  • 来源
    《Energy Conversion & Management》 |2014年第2期|508-517|共10页
  • 作者单位

    Department of Electrical and Electronic Engineering, South University of Science and Technology of China, Shenzhen 518055, China;

    Department of Electrical and Electronic Engineering, South University of Science and Technology of China, Shenzhen 518055, China;

    School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China;

    Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Horn, Kowloon, Hong Kong;

    Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong;

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

    Electric vehicle; Charging strategy; Vehicle-to-grid; Smart grid; Load variance; Regional grid;

    机译:电动汽车;充电策略;车辆到电网;智能电网;负载变化;区域网格;

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