面向港口关键起重设备调峰的协调优化运行方法

王枭; 赵山峰; 张乾能; 樊锐; 袁成清; 任海东

doi:10.3963/j.jssn.1674-4861.2025.06.014

面向港口关键起重设备调峰的协调优化运行方法

doi: 10.3963/j.jssn.1674-4861.2025.06.014

王枭^1,,
赵山峰²,
张乾能^{3, 4},
樊锐¹,
袁成清^3, ,,
任海东⁴

1.
武汉理工大学自动化学院武汉 430072
2.
三一海洋重工有限公司广东珠海 519000
3.
武汉理工大学交通与物流工程学院武汉 430063
4.
宁波舟山港集团有限公司浙江宁波 316000

基金项目:

国家重点研发计划项目 2024YFB4303502

详细信息

作者简介:
王枭（1990—），博士，副教授. 研究方向: 能源电力系统运行控制. E-mail：xwang90@whut.edu.cn

通讯作者:
袁成清（1976—），博士，教授. 研究方向: 船舶动力系统、港口新能源技术等. E-mail：ycq@whut.edu.cn

中图分类号: TM614
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出版历程
- 收稿日期: 2025-09-12
- 网络出版日期: 2026-03-13

A Coordinated Optimization Method for Peak-Shaving Operation of Key Port Crane Equipment

1.
School of Automation, Wuhan University of Technology, Wuhan 430072, China
2.
SANY Marine Heavy Industry Co., Ltd., Zhuhai 519000, Guangdong, China
3.
School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
4.
Ningbo Zhoushan Port Group Co., Ltd., Ningbo 316000, Zhejiang, China

摘要

摘要: 智能化和绿色化已成为未来港口发展的必然趋势。电气化改造后，港口关键设备均由港口微电网供电，安全稳定的电力供给是实现港口高效运输作业的保障。以自动化集装箱码头中的关键大型起重设备为研究对象，研究了1种面向港口微电网削峰填谷的作业协调优化调度策略。构建岸桥（ship-to-shore crane，STS）和轨道式场桥（rail-mounted gantry crane，RMG）的通用负荷计算模型，根据设备双循环作业周期的阶段划分，形成标准工况下的多阶段、全时域负荷曲线。在负荷建模的基础上，结合港口集中式储能的充放电能力，提出了起重设备集群作业周期与储能系统协同运行的精确优化模型；通过引入逻辑变量刻画多机设备所处的运行阶段与功率水平，构建考虑设备集群聚合功率冲击的约束条件与目标函数；求解优化模型获得多台设备的最优启动时刻，实现港口装备集群负荷波动平抑与能量利用效率提升。针对设备运行和储能容量配置进行了仿真分析，验证了多设备协调调度方法能够有效抑制峰谷差，在所考虑的场景下峰值功率下降20%以上。通过精确优化算法和启发式优化算法的比较分析，验证了精确优化方法的最优性与扩展能力；同时，给出了设备随机运行时的启动时刻可行域，明确了非理想情况下安全启动组合，给出了非标准工况下所提优化模型的扩展，体现出良好的工程实用价值。
- 港口微电网 /
- 起重设备 /
- 削峰填谷 /
- 精确优化
Abstract: Intelligent and green development is an inevitable trend for future port development. After electrification upgrades, key port equipment is supplied by the port microgrid, and a safe and stable power supply is the foundation for efficient port transportation operations. Focusing on critical large-scale port cranes in automated container terminals, this study investigates a coordinated operational scheduling strategy for peak shaving and valley filling in port microgrids. A unified load-calculation model for ship-to-shore cranes (STS) and rail-mounted gantry cranes (RMG) is established. By dividing the stages of the equipment's dual-cycle operating process, a multi-stage, full-time-horizon load profile under standard working conditions is developed. Building on the load modeling and considering the charge-discharge capability of centralized port energy storage, an exact optimization model is proposed for the coor-dinated operation between the operating cycles of crane clusters and the energy storage system. Logical variables are introduced to characterize the operating stage and power level of each machine, and constraints and an objective function are formulated to account for aggregated power impacts from equipment clusters. Solving the optimization model yields the optimal start times for multiple machines, thereby smoothing load fluctuations of port equipment clusters and improving energy utilization efficiency. Simulation analyses are conducted for equipment operation and energy storage capacity configuration, verifying that the multi-equipment coordinated scheduling method can effectively reduce the peak-valley difference, achieving more than a 20% reduction in peak power in the considered scenarios. Comparative analyses between exact optimization and heuristic optimization validate the optimality and scalability of the exact approach. In addition, the feasible region of start times under stochastic equipment operation is provided, identifying safe start-time combinations under non-ideal conditions. An extension of the proposed optimization model to non-standard operating conditions is also presented, demonstrating strong engineering practicality.
- port microgrid /
- lifting equipment /
- peak shaving and valley filling /
- exact optimization

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图 1 宁波舟山港的岸桥和场桥设备

Figure 1. Ship-to-shore (STS) and rail-mounted gantry (RMG) cranes in Ningbo-Zhoushan port.

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图 2 STS和RMG在标准双循环作业下的负荷曲线

Figure 2. Load profiles of STS and RMG in double cycles

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图 3 无储能情况下港口起重设备集群协调运行

Figure 3. Cooperative operation of port cranes without energy storage

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图 4 PSO算法的收敛过程

Figure 4. The convergence of the PSO algorithm

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图 5 精确优化下STS设备集群与储能系统协调运行

Figure 5. Cooperative operation of cranes with energy storage using exact optimization

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图 6 PSO优化下STS设备集群与储能系统协调运行

Figure 6. Cooperative operation of cranes with energy storage using the PSO algorithm

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图 7 港口设备集群注入功率约束下储能容量的优化配置

Figure 7. Optimal sizing energy storage under the constrained power injections of port cranes

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图 8 STS和RMG启动时刻的可行域

Figure 8. Feasible regions of start times for STS and RMG

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图 9 实际工况下3台STS设备的功率负荷曲线

Figure 9. Power load profiles of 3 STS devices under realistic working condition

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图 10 实际工况下3台STS的协调运行效果

Figure 10. Coordinated operation of 3 STS devices under realistic working condition

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表 1 双循环作业下STS的运行阶段与运行时间

Table 1. STS operational stages and time in double cycle

带载状态	循环作业阶段	加速、匀速、减速时间/s
带载状态	循环作业阶段	起升机构	小车
满载（集卡到船舱）	A：对接集装箱	5.0
	B：上升逆风向外移动	2.5/7.5/2.5	6.0/5.4/6.0
	C：下降到导向轨上方	1.8/0/1.8	6.0/5.4/6.0
	D：进入导向轨	2
	E：继续下降并停止	2.5/5.1/2.5
空载（船舱内取箱）	F：脱离集装箱	5.0
	G：起升机构上升	4.5/0/4.5	2.1/0/2.1
	H：逆风移动
	I：下降到导向轨上方	1.3/0/1.3
	J：进入导向轨	2.0
	K：继续下降并停止	4.3/0/4.3
满载（船舱到集卡）	L：对接集装箱	5.0
	M：起升机构上升	2.5/6.4/2.5	6.0/4.7/6.0
	N：下降顺风向内移动	2.5/7.1/2.5
	O：下降到运输集卡	1.3/0/1.3
空载（集卡取箱）	P：脱离集装箱	5.0
	Q：起升机构上升	1.3/0/1.3	2.7/0/2.7
	R：向内顺风移动
	S：下降到码头集装箱	1.3/0/1.3

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表 2 精确优化与PSO算法的求解效果比较

Table 2. Comparison of the exact optimization and the PSO algorithm

设备数量		5	10	20
设备数量		Gurobi/PSO
STS	峰值功率/kW	2 326/2 414	3 846/3 405	-/5484
STS	计算时间/s	28/0.7	3 000/0.9	-/3.6
RMG	峰值功率/kW	2 949/3 115	5 832/6 230	-/11 987
RMG	计算时间/s	140/0.8	3 000/1.6	-/5.9

下载: 导出CSV

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