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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
Abstract   (2058 HTML8 PDF(pc) (3702KB)(557)  

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.6 AGV charging results in parallel operation of multi-quay cranes
Extracts from the Article
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EminEmax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EminEmax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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