Joint Economic Optimization of AGV Logistics Scheduling and Orderly Charging in a Low-Carbon Automated Terminal
WANG Xuan, WANG Bao, CHEN Yanping, LIU Hong, MA Xiaohui
Journal of Shanghai Jiao Tong University
2024, 58 ( 9):
1370-1380.
DOI: 10.16183/j.cnki.jsjtu.2023.027
To improve the current automated guided vehicle (AGV) charging strategy at automated terminals, which is not fully coordinated with the distributed power supply, a joint optimization method of AGV logistics scheduling and orderly charging is proposed. First, the synergetic relationship between AGV logistics scheduling and charging scheduling is analyzed, and a joint optimization framework is built. Then, a method to calculate the distance traveled by AGVs while considering the segregation requirements of trucks inside and outside the terminal is proposed. Afterwards, for the AGV charging module, the judgment conditions of AGV charging status and the pile selection method are defined. Furthermore, to minimize the cost of purchasing electricity at the terminal, a joint optimization model of logistics scheduling and orderly charging is constructed by considering time-of-use tariff, distributed power feed-in tariff, power balance constraint, state of charge constraint at the termination moment, upper and lower bound constraints of decision variables, and logistics scheduling constraint. Finally, a fast solution method based on improved particle swarm optimization algorithm is proposed, of which the effectiveness and economic efficiency are verified by an actual case of a terminal.
Fig.1
Layout of automated container terminal
Extracts from the Article
(1) 物流调度的作业流程. 当船舶到港时,由调度系统指定船舶停靠泊位,并提前分配好相应的岸桥,指派满足电量要求的AGV到指定的岸桥位置等待.待岸桥将集装箱装卸至AGV后,由AGV自动行驶至堆场内指定位置,并等待轨道桥卸放集装箱至目的地,即完成本轮任务.然后,AGV保持就地不动,等待下轮指派.自动化码头布局示意图如图1所示.自动化码头可分为A、B、C三个区域,为保证AGV无人驾驶的安全性,需将其所行驶的道路与外部集卡道路隔离[19],且在堆场侧AGV只能由西向东单向行驶,在岸桥侧方可双向行驶.当AGV与外部集卡交汇在道路重合部分时,AGV启动自动识别和等待功能,待外部集卡通过后方可继续行驶,如图1中箭头所示.例如:当停在C区堆场侧的AGV到A区岸桥侧时,需先返回至C区岸桥侧后行驶至A区岸桥侧.因此在进行物流调度建模时需考虑行驶路径要求.
由于岸桥并行作业数决定了AGV物流调度的需求量,所以本算例采用联合优化方法分别选取1、3、5、7座岸桥进行并行作业调度,起始SOC均为95%,调度结束时刻SOC均值不低于75%,求解出各场景下的决策变量区间,如图6所示.由图可见,当岸桥数为1座和3座时,寻优的Emin和Emax区间差值分别为28%和34%,说明对充电电量要求低,从频次较低可以看出物流可调度AGV充裕;当岸桥数为5座和7座时,寻优的Emin和Emax区间差值分别为55%和57%,说明对充电量需求提高,且从充电频次增多可以看出,随着岸桥并行作业数量的提高,AGV消耗电量增多,充电时长从短时段递进为长时段以保证物流调度作业的连续性和稳定性,从而提升优化效果.
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