Joint Strategy of Computation Offloading and Energy Management for Electric Vehicle Based on Mean Field Game

HU Lei; ZHANG Yuyan; ZHANG Biling; LIU Jiahua; JIA Dongqiang

doi:10.7500/AEPS20220614010

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Joint Strategy of Computation Offloading and Energy Management for Electric Vehicle Based on Mean Field Game

Basic Research | 更新时间：2025-06-16

- Joint Strategy of Computation Offloading and Energy Management for Electric Vehicle Based on Mean Field Game
- Automation of Electric Power Systems Vol. 47, Issue 7, Pages: 123-132(2023)
- 作者机构：
  
  1.北京邮电大学网络教育学院，北京市100876
  2.国网北京市电力公司，北京市 100031
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(62171060)
- DOI：10.7500/AEPS20220614010
  CLC：
- Received：14 June 2022，
  
  Revised：2022-12-04，
  
  Published Online：08 March 2023，
  
  Published：10 April 2023
- 稿件说明：
移动端阅览
胡蕾,张玉艳,张碧玲等.基于平均场博弈的电动汽车计算卸载及能源管理联合策略[J].电力系统自动化,2023,47(7):123-132.

HU Lei,ZHANG Yuyan,ZHANG Biling,et al.Joint Strategy of Computation Offloading and Energy Management for Electric Vehicle Based on Mean Field Game[J].Automation of Electric Power Systems,2023,47(7):123-132.
胡蕾,张玉艳,张碧玲等.基于平均场博弈的电动汽车计算卸载及能源管理联合策略[J].电力系统自动化,2023,47(7):123-132. DOI： 10.7500/AEPS20220614010.

HU Lei,ZHANG Yuyan,ZHANG Biling,et al.Joint Strategy of Computation Offloading and Energy Management for Electric Vehicle Based on Mean Field Game[J].Automation of Electric Power Systems,2023,47(7):123-132. DOI： 10.7500/AEPS20220614010.

摘要

在能源互联网中，电动汽车(EV)不仅是一种能够参与能源需求响应的分布式移动能源节点，也是一种能够执行计算任务并通过无线传输将部分任务卸载给移动边缘计算(MEC)中心的计算节点。由于计算耗能不可忽略，文中从优化成本的角度考虑具有计算需求及能源需求的大规模EV的计算卸载及能源管理问题。考虑到EV的传输速率和充放电功率等策略受其他EV策略的影响，将EV的决策过程建模为平均场博弈(MFG)模型。首先，定义并计算MEC计算价格、传输干扰和瞬时电价等平均场项；然后

通过求解HJB-FPK方程组得到基于MFG的最优计算卸载及能源管理策略。算例分析结果表明了所提策略不仅具有最优的经济效益，而且在维护电网稳定运行方面具有明显的优越性。

Abstract

In the Energy Internet

electric vehicles (EVs) are not only the distributed mobile energy nodes that can participate in the energy demand response (DR)

but also the computing nodes that can perform computation tasks and offload some tasks to the mobile edge computing (MEC) center via wireless transmission. Since the computational energy consumption can not be ignored

this paper considers the computation offloading and energy management of massive EVs with computation and energy demands from the perspective of optimizing cost. Considering that the strategies of transmission rate and charging/discharging power of an EV are affected by those of other EVs

the decision-making process of EVs is formulated into a mean field game (MFG). First

the mean field items of the computation price of MEC

transmission interference

and instantaneous electricity price are defined and calculated. Then

the optimal computation offloading and energy management strategy based on MFG are obtained by solving the Hamilton-Jacobi-Bellman-Fokker-Planck-Kolmogorov (HJB-FPK) equations. Simulation analysis results show that the proposed strategy not only can obtain the optimal economic benefits but also are superior in maintaining the stable operation of the power grid.

关键词

Keywords

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