| 引用本文: | 顾延勋,林晓明,廖雁群,等.计及电动汽车边缘计算的配电网与充电站分层运行优化方法[J].电力系统保护与控制,2025,53(6):63-73.[点击复制] |
| GU Yanxun,LIN Xiaoming,LIAO Yanqun,et al.Hierarchical operation optimization method for distribution networks and charging stations considering edge computing in electric vehicles[J].Power System Protection and Control,2025,53(6):63-73[点击复制] |
|
| 摘要: |
| 电动汽车(electric vehicle, EV)电池技术的突破以及车载算力的不断提高，使得EV同时具备移动储能与边缘计算的双向互动能力。考虑EV移动储能与边缘计算的双重属性，引入“充电计算站(charging and computing station, CCS)”的概念，提出了基于目标级联法(analytical target cascading, ATC)的配电网与充电站分层运行优化模型。首先，建立了CCS的EV充放电及边缘计算能耗模型。进一步以最小化CCS和配电网的运行成本为目标，构建了包含多个CCS的配电网潮流优化模型，实现EV充放电功率、边缘服务器任务卸载和计算资源分配的最优决策。其次，设计了基于ATC算法的配电网与CCS的分层运行优化计算方法，既使得CCS能够自主进行电能和计算管理，又保障了每个CCS的本地数据隐私。最后，仿真结果表明，所提优化模型可以通过聚合EV计算资源协助边缘服务器完成更多计算任务，有效提升CCS的计算收益。同时通过EV充放电及边缘服务器用电的优化决策，进一步降低系统整体运行成本。 |
| 关键词: 配电网 充电站 边缘计算 分层优化 |
| DOI：10.19783/j.cnki.pspc.240458 |
| 投稿时间：2024-04-16修订日期：2024-10-11 |
| 基金项目:南方电网公司科技项目资助(GDKJXM20222215)；国家重点研发计划项目资助(2019YFE0118700) |
|
| Hierarchical operation optimization method for distribution networks and charging stations considering edge computing in electric vehicles |
| GU Yanxun1,LIN Xiaoming2,3,LIAO Yanqun1,ZHANG Fan2,3,LAI Zhe1,TANG Jianlin2,3 |
| (1. Zhuhai Power Supply Bureau of Guangdong Power Grid Co., Ltd., Zhuhai 519000, China; 2. Electric Power
Research Institute, CSG, Guangzhou 510670, China; 3. Guangdong Provincial Key Laboratory of Intelligent
Measurement and Advanced Metering of Power Grid, Guangzhou 510670, China) |
| Abstract: |
| Breakthroughs in electric vehicle (EV) battery technology and the continuous enhancement of onboard
computing power enable EVs to possess dual capabilities of mobile energy storage and edge computing. This paper
considers the dual attributes of EVs as mobile energy storage and edge computing resources, and introduces the concept
of “charging and computing station (CCS)”. Based on the analytical target cascading (ATC) method, a hierarchical
operation optimization model for the distribution network and charging stations is proposed. First, an energy consumption
model for EV charging/discharging and edge computing within a CCS is established. Then, aiming to minimize the
operating costs of a CCS and the distribution network, a power flow optimization model for the distribution network
incorporating multiple CCSs is constructed to achieve optimal decision-making for EV charging/discharging power, edge
server task offloading, and computing resource allocation. Second, a hierarchical operation optimization calculation
method for the distribution network and CCS based on the ATC algorithm is designed, enabling CCSs to perform
autonomous energy and computing management while protecting the local data privacy of each CCS. Finally, simulation
results demonstrate that the proposed optimization model can effectively enhance the computing revenue of a CCS by
aggregating EV computing resources to assist edge servers in completing more computational tasks. Additionally, by
optimizing EV charging/discharging and edge server power consumption, the overall system operating cost is further reduced. |
| Key words: power distribution network charging station edge computing hierarchical optimization |
