半月刊

ISSN 1000-1026

CN 32-1180/TP

+高级检索 English
计及电池损耗的电动公交车参与V2G的优化调度策略
作者:
作者单位:

1.东南大学电气工程学院,江苏省南京市 210096;2.国网江苏省电力有限公司常熟市供电分公司,江苏省常熟市 215500;3.国网江苏省电力有限公司苏州市供电分公司,江苏省苏州市 215000;4.中国电力科学研究院有限公司(南京),江苏省南京市 210003

作者简介:

通讯作者:

基金项目:

国家自然科学基金资助项目(51607098)。


Battery Loss Based Optimal Dispatching Strategy of Electric Bus Participating in Vehicle-to-grid
Author:
Affiliation:

1.School of Electrical Engineering, Southeast University, Nanjing 210096, China;2.Changshu Power Supply Company of State Grid Jiangsu Electric Power Co., Ltd., Changshu 215500, China;3.State Grid Suzhou Power Supply Company of State Grid Jiangsu Electric Power Co., Ltd., Suzhou 215000, China;4.China Electric Power Research Institute (Nanjing), Nanjing 210003, China

Fund Project:

This work is supported by National Natural Science Foundation of China (No. 51607098).

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
    摘要:

    考虑动力电池的损耗成本,提出一种电动公交车参与电动汽车与电网互动(V2G)的多时间尺度优化调度策略。首先,依据工程经济学原理建立动力电池的损耗模型。然后,在日前阶段的上层以公交公司的日运营成本最小为目标,采用迭代法对电池损耗成本和充电站的充放电计划进行联动优化;下层模型在上层优化结果的基础上,以配电网负荷峰谷差最小为目标,进一步优化充电站的充放电计划。日内阶段对光伏出力和配电网基础负荷功率进行滚动更新,以公交公司日运营成本最小和日前、日内计划偏差最小为目标对日前计划进行修正。最后,从公交公司和电网2个角度对无序充电、有序充电、参与V2G的3种方案进行对比分析,验证了电动公交车参与V2G时的优越性,并通过灵敏度分析表明不同V2G补偿系数下公交公司运营成本的变化趋势。

    Abstract:

    Considering the loss cost of power batteries, a multi-time scale optimal scheduling strategy of electric buses participating in vehicle-to-grid (V2G) is proposed. Firstly, based on the principle of engineering economics, a loss model of power battery is established. In order to optimize both the battery loss cost and the charging-discharging plan of charging station, an iterative method is adopted to minimize the daily operating cost of the bus company in upper layer of day-ahead stage. Based on results optimized in upper layer, the charging-discharging plan of charging station is further optimized to minimize the peak-to-valley difference of distribution network. In the intraday stage, the output power of photovoltaic (PV) and the base load power of distribution network are rolling updated, the day-ahead plan is revised in order to minimize the daily operating cost of bus company and the deviation between day-ahead plan and intraday plan. Finally, from the perspectives of bus company and power grid, three strategies of disordered charging, orderly charging and participating in V2G are compared and analyzed to verify the superiority of electric bus participating in V2G. The changing trend of the operating cost of bus company with different V2G compensation coefficients is reflected by sensitivity analysis.

    表 5 Table 5
    表 1 3种方案下的相关成本比较Table 1 Comparison of relevant cost in three schemes
    表 3 Table 3
    表 4 Table 4
    图1 多时间尺度优化调度架构Fig.1 Architecture of multi-time scale optimal scheduling
    图2 3种方案下充电站的充放电电量统计图Fig.2 Statistical diagram of charging and discharging electric quantity for charging station in three schemes
    图3 方案3的双层配电网总负荷曲线Fig.3 Double-layer total load curves of distribution network in scheme 3
    图 动力电池的现金流量图Fig. Cash flow diagram of power battery
    图 多时间尺度优化调度时间框架Fig. Time framework of multi-time scale optimal scheduling
    图 电动公交车充电站多时间尺度优化调度流程图Fig. Flow chart of multi-time scale optimal scheduling for electric bus charging station
    图 3种方案下充电站的充放电功率Fig. Charging and discharging power of charging station in three schemes
    图 方案3中每辆电动公交车的电量分布图Fig. Electricity distribution diagram of each electric bus in scheme 3
    图 方案3中上层阶段的迭代图Fig. Iterative diagram of upper-level stage in scheme 3
    图 充电站的充放电功率修正图Fig. Correction diagram of charging and discharging power of charging station
    表 2 不同补偿下的各项成本Table 2 Various costs in different compensations
    参考文献
    相似文献
    引证文献
引用本文

陈丽娟,秦萌,顾少平,等.计及电池损耗的电动公交车参与V2G的优化调度策略[J/OL].电力系统自动化,http://doi.org/10.7500/AEPS20190730003.
CHEN Lijuan,QIN Meng,GU Shaoping,et al.Battery Loss Based Optimal Dispatching Strategy of Electric Bus Participating in Vehicle-to-grid[J/OL].Automation of Electric Power Systems,http://doi.org/10.7500/AEPS20190730003.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2019-07-30
  • 最后修改日期:2020-02-23
  • 录用日期:2019-11-18
  • 在线发布日期:
  • 出版日期: