Collaborative Scheduling Strategy of Truck Mobile Charging Station Based on Information Gap Decision Theory

HE Kecheng; JIA Hongjie; MU Yunfei; YU Xiaodan; XIAO Qian; DONG Xiaohong

doi:10.7500/AEPS20231007005

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Collaborative Scheduling Strategy of Truck Mobile Charging Station Based on Information Gap Decision Theory

Basic Research | 更新时间：2025-06-16

- Collaborative Scheduling Strategy of Truck Mobile Charging Station Based on Information Gap Decision Theory
- Automation of Electric Power Systems Vol. 48, Issue 15, Pages: 44-53(2024)
- 作者机构：
  
  1.智能电网教育部重点实验室（天津大学），天津市 300072
  2.兰州交通大学新能源与动力工程学院，甘肃省兰州市 730070
  3.省部共建电工装备可靠性与智能化国家重点实验室（河北工业大学），天津市 300131
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(52277116);National Natural Science Foundation of China(U22B20105);the seed Foundation of Tianjin University(2023XSU-0025)
- DOI：10.7500/AEPS20231007005
  CLC：
- Received：07 October 2023，
  
  Revised：2024-02-24，
  
  Published Online：10 April 2024，
  
  Published：10 August 2024
- 稿件说明：
移动端阅览
何克成,贾宏杰,穆云飞等.基于信息间隙决策理论的卡车式移动充电站协同调度策略[J].电力系统自动化,2024,48(15):44-53.

HE Kecheng,JIA Hongjie,MU Yunfei,et al.Collaborative Scheduling Strategy of Truck Mobile Charging Station Based on Information Gap Decision Theory[J].Automation of Electric Power Systems,2024,48(15):44-53.
何克成,贾宏杰,穆云飞等.基于信息间隙决策理论的卡车式移动充电站协同调度策略[J].电力系统自动化,2024,48(15):44-53. DOI： 10.7500/AEPS20231007005.

HE Kecheng,JIA Hongjie,MU Yunfei,et al.Collaborative Scheduling Strategy of Truck Mobile Charging Station Based on Information Gap Decision Theory[J].Automation of Electric Power Systems,2024,48(15):44-53. DOI： 10.7500/AEPS20231007005.

摘要

卡车式移动充电站（TMCS）由于具有良好的移动储能及调度灵活性已经引起国内外业界的高度关注，而其潜在的应用价值尚未得到充分挖掘。为此，提出一种基于信息间隙决策理论（IGDT）的TMCS协同优化调度策略，以协调其在为电动汽车充电服务和电网能量套利之间的协同运行。根据运营商对风险的偏好程度，分别建立鲁棒IGDT模型和机会IGDT模型，在不同风险态度下

探讨了电动汽车充电需求以及电网注入功率的不确定性对运营商优化调度方案的影响。算例分析表明，所提方法能够为考虑多重不确定因素的TMCS优化调度决策提供有效支撑，在兼顾充电服务质量的同时保障充电设施运营商的收益。

Abstract

The truck mobile charging station (TMCS) has gained significant attention for its mobile energy storage and scheduling flexibility in domestic and foreign industry

but its potential commercial applications have yet been fully explored. Therefore

a collaborative scheduling strategy of TMCS based on information gap decision theory (IGDT)

which coordinates its operation between electric vehicle charging services and grid energy arbitrage

is proposed. According to the operator’s preference for risk

a robust IGDT model and an opportunistic IGDT model are developed

respectively. The impact of uncertainty in electric vehicle charging demand as well as grid-injected power on operator’s optimal scheduling scheme is explored under different risk attitudes. The case analysis shows that the proposed method can provide effective support for optimal scheduling decisions of TMCS considering multiple uncertainties. The revenue of charging facility operators and the charging service quality are ensured.

关键词

Keywords

references

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