微电网
计算机科学
调度(生产过程)
车队管理
能源消耗
运筹学
端口(电路理论)
地铁列车时刻表
运营管理
工程类
电信
操作系统
电气工程
人工智能
控制(管理)
作者
A. Lin,Shuli Wen,Miao Zhu,Xiaochi Cai
出处
期刊:IEEE transactions on intelligent vehicles
[Institute of Electrical and Electronics Engineers]
日期:2023-11-24
卷期号:9 (1): 752-763
被引量:2
标识
DOI:10.1109/tiv.2023.3336523
摘要
All-electric ship fleets, which are distinct from landbased microgrid clusters, operate as maritime mobile microgrid clusters, navigating among multiple ports to satisfy various spatial-temporally logistics service demands of each port. In this context, unlike a traditional ship fleet dispatching problem which only focuses on logistics, a joint optimal energy management and logistic scheduling is proposed in this paper, taking into account the navigation risk. To minimize the operation costs while ensuring the logistics service quality, a hierarchical coordinated optimization framework is proposed to jointly optimize the logistics scheduling and energy management, adhering to navigation safety guidelines. Within this framework, novel riskaware port-to-port paths are determined using a specific graph search algorithm tailored for multi-port maritime transportation, guaranteeing the safety and reliability of each all-electric ship (AES). The optimal logistics scheduling, including spatialtemporal trip chains for AESs in the fleet, is performed to reduce turnaround time. Furthermore, in order to improve the operational performance of ship fleets, an advanced energy management integrated with voyage speed adjustment is employed to minimize fuel consumption and greenhouse gas emissions for each AES. Numerical results reveal that with the help of the proposed coordinated optimization algorithm, both economic costs and carbon emissions are efficiently reduced with highquality logistics services.
科研通智能强力驱动
Strongly Powered by AbleSci AI