电力系统自动化2026，Vol.50Issue(16)：66-76,11.DOI:10.7500/AEPS20251005001
考虑车辆路径约束的港口微电网电动转运车充电调度方法
Charging Scheduling Method for Electric Transfer Vehicles in Port Microgrids Considering Vehicle Path Constraints
摘要
Abstract
Electric transfer vehicles(ETVs),which serve as critical logistics equipment connecting quay areas and yard areas,pose severe challenges to port micro grids in cost reduction and energy consumption minimization due to their uncoordinated charging.To address these challenges,this paper explores the charging flexibility of ETVs and proposes a charging scheduling method for ETVs considering conflict-free path constraints and battery health constraints,with the objective of minimizing task delay penalties and charging costs.Meanwhile,to mitigate battery life degradation caused by frequent and deep charging-discharging cycles,a linear battery healthy operating region is constructed via hyperplane projection and convex approximation techniques,which is compatible with the proposed port ETV charging model without introducing extra computational complexity.Furthermore,to handle the combinatorial decision-making complexity arising from the strong coupling among path,charging,and energy constraints,the port ETV scheduling process is formulated as a multi-agent Markov decision process under a rolling-horizon framework.A Q-learning-based multi-agent reinforcement learning framework is then employed to realize collaborative optimization between vehicle-level decision-making and system-level optimization,thereby effectively reducing the solution scale and improving overall scheduling efficiency.Finally,numerical analyses based on a practical port are carried out to verify the effectiveness and practicability of the proposed method.关键词
微电网/电动转运车辆/路径约束/强化学习/电池健康/多智能体/充电成本/马尔可夫决策过程Key words
microgrid/electric transfer vehicle(ETV)/path constraint/reinforcement learning/battery health/multi-agent/charging cost/Markov decision process引用本文复制引用
卢莹,方斯顿,牛涛,陈冠宏,廖瑞金..考虑车辆路径约束的港口微电网电动转运车充电调度方法[J].电力系统自动化,2026,50(16):66-76,11.基金项目
国家电网有限公司总部科技项目(5400-202418219A-1-1-ZN). This work is supported by State Grid Corporation of China(No.5400-202418219A-1-1-ZN). （5400-202418219A-1-1-ZN）
