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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.


参数 取值 参数 取值
n/辆 76 E m i n m i n, E m i n m a x/% 20, 60
npile/桩 13 E m a x m i n, E m a x m a x/% 60, 100
σ 7 t2/min 4
Ploss/(kW·h·km-1) 3.7 (xA, left, xA, right)/m (0, 296)
Ptotal/(kW·h) 282 (xB, left, xB, right)/m (355, 652)
v/(m·s-1) 4 (xC, left, xC, right)/m (711, 1 008)
t1/min 1 pchar,1, pchar,2/kW 234, 109
Tab.3 Parameters of scheduling model
Extracts from the Article
设置粒子数30个,迭代次数100次,ω1表示η=1情况下的初值为1,ωa为0.95,c1、c2均为1.5,速度变量的变化系数φ为0.3,调度模型参数如表3所示.表中:pchar,1pchar,2分别为SOC小于、大于等于80%时的充电功率.分时电价分别为峰时段(09:00-12:00,16:00-21:00) 0.919 67元/(kW·h)、谷时段(23:00-07:00) 0.331 47元/(kW·h)、平时段(07:00-09:00,12:00-16:00,21:00-23:00) 0.636 87元/(kW·h),风光上网电价为 0.365 5 元/(kW·h).
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