储能科学与技术 ›› 2020, Vol. 9 ›› Issue (1): 195-203.doi: 10.19799/j.cnki.2095-4239.2019.0140

• 储能系统与工程 • 上一篇    下一篇

复杂运营环境下快充型公交充电策略优化方法

周 丹(), 任志伟1, 孙 可, 陈锡祥2, 郑伟民2   

  1. 1. 浙江工业大学信息学院,浙江 杭州 310023
    2. 国网浙江省电力有限公司,浙江 杭州 310007
  • 收稿日期:2019-06-21 修回日期:2019-09-02 出版日期:2020-01-05 发布日期:2019-09-03
  • 作者简介:主要研究方向为储能并网、可再生能源消纳技术,E-mail:zhoudan@zjut.edu.cn
  • 基金资助:
    浙江省重点研发计划项目(2019C01149)

Optimization method of fast charging buses charging strategy for complex operating environment

ZHOU Dan(), REN Zhiwei1, SUN Ke, CHEN Xixiang2, ZHENG Weimin2   

  1. 1. College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China
    2. State Grid Zhejiang Electric Power Co. , Ltd. , Hangzhou 310007, Zhejiang, China
  • Received:2019-06-21 Revised:2019-09-02 Online:2020-01-05 Published:2019-09-03

摘要:

纯电动公交车已逐渐成为城市公共交通的主要工具,如何实现快速及时的电能补给同时避免电网系统在安全性和经济性方面受到影响是当前发展中面临的一个重要问题。在考虑复杂运营环境中影响充电策略的多种因素基础上,利用双层优化模型和滚动优化方法,本工作提出了一种纯电动公交车充电策略优化方法。首先建立了以充电费用和电池损耗成本为目标的快速充电双层优化模型,上层模型预测层根据日前公交车期望满载率、交通指数和分时电价等预测数据给出纯电动公交车日前充电计划,下层模型调度层根据实时运营数据对日前充电计划进行滚动优化。MATLAB的仿真结果验证了所提出的方法可以有效优化纯电动公交车充电过程,提高纯电动公交车快速充电的经济性,同时降低大量纯电动公交车集中充电对电网造成的影响。

关键词: 纯电动公交车, 有序充电, 双层优化模型, 间歇充电, 滚动优化, 充电成本

Abstract:

Pure electric buses have gradually become the main mode of urban public transport in China. One of the key issues associated with this development is how to provide rapid and timely electric power supply for the electric buses while avoiding the potential safety and economic impacts associated with a power grid system. This study proposes a charging strategy optimization method for pure electric buses using a double-level optimization model and a rolling optimization method while considering multiple factors that affect the charging strategy in a complex operating environment. First, this study establishes a two-tier optimization model for rapidly charging pure electric buses, aiming to minimize the costs associated with the charging and battery loss. The upper tier predicts a forecast charging plan for pure electric buses based on the expected full load rate, traffic index and time-of-use electricity cost. The lower tier is the model-dispatching level, which performs rolling optimization of the forecasted charging plan according to the real-time operation data. The MATLAB simulation results reveal that the proposed method can effectively optimize the pure electric bus charging process, improve the economy of rapid charging, and reduce the impact of concentrated charging of a large number of pure electric buses on the power grid.

Key words: pure electric bus, coordinated charging, two-layer optimization model, intermittent charging, rolling optimization, charging costs

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