Two-Stage Optimization Strategy Considering Ship Resilient Voyage Programming and Power Generation Scheduling

doi:10.16183/j.cnki.jsjtu.2024.275

Abstract

Abstract:

For oceanic island clusters with special geographical conditions, this paper proposes a rescue vessel scheduling strategy that integrates island transportation and energy supply to address resource heterogeneity among oceanic island clusters and ensure vessel safety, thereby improving the disaster resilience of rescue vessels under optimized scheduling. Based on both energy dispatch and transportation, a two-stage optimization method is adopted. In the first stage, day-ahead scheduling is performed according to the geographical relationship of the islands to determine preliminary sailing routes. In the second stage, both safe and emergency modes are considered. In the safe mode, based on the optimized routing information from the first stage, further optimal scheduling of power generation is performed to improve operational efficiency and economic performance under environmental constraints. In the emergency mode, considering generator fault, a coordinated optimization strategy between load-side management and power generation is implemented to support critical rigid loads and guarantee the normal operation of rescue vessels. Finally, simulation results verify the effectiveness of the proposed strategy, providing a theoretical reference for the sustainable development and construction of oceanic island clusters.

Key words: rescue vessel, optimized scheduling, disaster resilience, two-stage optimization, load-side ma~nagement

CLC Number:

TM732

ZHOU Lidan, ZHENG Hang, YU Tianyou, WANG Jie. Two-Stage Optimization Strategy Considering Ship Resilient Voyage Programming and Power Generation Scheduling[J]. Journal of Shanghai Jiao Tong University, 2026, 60(6): 892-903.

Figures/Tables 15

Fig.1

Fig.2

Fig.3

Fig.4

Tab.1

Tab.2

Fig.5

Fig.6

Tab.3

Tab.4

Fig.7

Fig.8

Tab.5

Fig.9

Fig.10

References 30

[1]	裴正强, 刘春玲, 李冬. 船舶救生艇柴油机燃油系统进气故障及排除[J]. 中国修船, 2021, 34(1): 29-31.
	PEI Zhengqiang, LIU Chunling, LI Dong. Trouble and troubleshooting of diesel engine fuel system in ship lifeboat[J]. China Shiprepair, 2021, 34(1): 29-31.
[2]	孙晓军, 宋恩哲, 姚崇. 船用混合动力推进系统能量管理系统关键技术研究现状[J]. 中国机械工程, 2022, 33(4): 469-481.
	SUN Xiaojun, SONG Enzhe, YAO Chong. Research status of key technologies for energy management system of marine hybrid propulsion systems[J]. China Mechanical Engineering, 2022, 33(4): 469-481.
[3]	卓振宇, 张宁, 谢小荣, 等. 高比例可再生能源电力系统关键技术及发展挑战[J]. 电力系统自动化, 2021, 45(9): 171-191.
	ZHUO Zhenyu, ZHANG Ning, XIE Xiaorong, et al. Key technologies and developing challenges of power system with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2021, 45(9): 171-191.
[4]	中华人民共和国海事局. 关于印发船舶能耗数据和碳强度管理办法的通知[EB/OL]. (2022-11-24)[2024-07-04]. https://www.msa.gov.cn/page/article.do?articleId=E40C898D-11DD-41E4-8D97-72062C28D65B.
	Maritime Safety Administration of the People’s Republic of China. Notice on the issuance of the measures for the administration of ship energy consumption data and carbon intensity[EB/OL] (2022-11-24)[2024-07-04]. https://www.msa.gov.cn/page/article.do?articleId=E40C898D-11DD-41E4-8D97-72062C28D65B.
[5]	International Maritime Organization. Adoption of the initial IMO strategy on reduction of GHG emissions from ships and existing IMO activity related to reducing GHG emissions in the shipping sector[EB/OL]. (2018-04-13)[2024-07-04]. https://unfccc.int/sites/default/files/resource/250_IMOsubmission_TalanoaDialogue_April2018.pdf.
[6]	SUN X J, YAO C, SONG E Z, et al. A review of development of hybrid power systems and intelligent energy management control strategies for ships[J]. Journal of Propulsion Technology, 2022, 43(7): 24-46.
[7]	吴云强, 张戎. 单向航道下连续泊位分配与船舶调度集成优化[J]. 计算机工程与应用, 2022, 58(9): 246-255. doi: 10.3778/j.issn.1002-8331.2009-0447
	WU Yunqiang, ZHANG Rong. Integrated optimization of continuous berth allocation and ship scheduling under one-way channe[J]. Computer Engineering and Applications, 2022, 58(9): 246-255. doi: 10.3778/j.issn.1002-8331.2009-0447
[8]	彭荣琦, 孔得朋, 庞文棣, 等. 救援海洋平台遇险落水人员的船舶调度优化方法[J]. 中国安全科学学报, 2022, 32(11): 208-215. doi: 10.16265/j.cnki.issn1003-3033.2022.11.1272
	PENG Rongqi, KONG Depeng, PANG Wendi, et al. Optimization method of ship dispatching for emergency rescue of personnel falling overboard on offshore platform[J]. China Safety Science Journal, 2022, 32(11): 208-215. doi: 10.16265/j.cnki.issn1003-3033.2022.11.1272
[9]	范厚明, 于佳琪, 马梦知, 等. 模糊时间窗下多船型不定期船调度与航速联合优化[J]. 上海交通大学学报, 2021, 55(3): 297-310. doi: 10.16183/j.cnki.jsjtu.2019.215
	FAN Houming, YU Jiaqi, MA Mengzhi, et al. Heterogeneous tramp ship scheduling and speed optimization with fuzzy time window[J]. Journal of Shanghai Jiao Tong University, 2021, 55(3): 297-310.
[10]	WANG X, YUAN Y, TONG L, et al. Energy management strategy for diesel-electric hybrid ship considering sailing route division based on DDPG[J]. IEEE Transactions on Transportation Electrification, 2023, 10(1): 187-202. doi: 10.1109/TTE.2023.3263328 URL
[11]	HOU H, GAN M, WU X, et al. Real-time energy management of low-carbon ship microgrid based on data-driven stochastic model predictive control[J]. CSEE Journal of Power and Energy Systems, 2023, 9(4): 1482-1492.
[12]	ZHAO T, QIU J, WEN S, et al. Efficient onboard energy storage system sizing for all-electric ship microgrids via optimized navigation routing under onshore uncertainties[J]. IEEE Transactions on Industry Applications, 2022, 58(2): 1664-1674. doi: 10.1109/TIA.2022.3145775 URL
[13]	WEN S, ZHAO T, TANG Y, et al. A joint photovoltaic-dependent navigation routing and energy storage system sizing scheme for more efficient all-electric ships[J]. IEEE Transactions on Transportation Electrification, 2020, 6(3): 1279-1289. doi: 10.1109/TTE.6687316 URL
[14]	XU L, GUERRERO J, LASHAB A, et al. A review of DC shipboard microgrids—Part II: Control architectures, stability analysis, and protection schemes[J]. IEEE Transactions on Power Electronics, 2022, 37(4): 4105-4120. doi: 10.1109/TPEL.2021.3128409 URL
[15]	SUN X, QIU J. Hierarchically coordinated voltage control in seaport microgrids considering optimal voyage navigation of all-electric ships[J]. IEEE Transactions on Transportation Electrification, 2022, 8(2): 2191-2204. doi: 10.1109/TTE.2021.3138204 URL
[16]	肖朝霞, 朱洪驰, 曹家宁, 等. 有源前端组网的直流船舶电网高能效运行控制[J]. 电力系统及其自动化学报, 2024, 36(1): 61-70.
	XIAO Zhaoxia, ZHU Hongchi, CAO Jianing, et al. High energy efficiency operation and control of DC shipboard grid with active front end networking[J]. Proceedings of the CSU-EPSA, 2024, 36(1): 61-70.
[17]	KUMAR N, PANDA S K. A multipurpose and power quality improved electric vessels charging station for the seaports[J]. IEEE Transactions on Industrial Informatics, 2022, 19(3): 3254-3261. doi: 10.1109/TII.2022.3170424 URL
[18]	TAO Y, QIU J, LAI S, et al. Flexible voyage scheduling and coordinated energy management strategy of all-electric ships and seaport microgrid[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 24(3): 3211-3222. doi: 10.1109/TITS.2022.3226449 URL
[19]	LIN A, WEN S, ZHU M, et al. Joint optimal energy management and voyage scheduling for economic and resilient operation of all-electric ships considering safe return[J]. IEEE Transactions on Industry Applications, 2023, 59(5): 5304-5313. doi: 10.1109/TIA.2023.3287968 URL
[20]	FANG C, YIN J, REN H. Evaluation model of ship berthing behavior based on AIS data[J]. IEEE Open Journal of Intelligent Transportation Systems, 2022, 3: 104-110. doi: 10.1109/OJITS.2021.3138562 URL
[21]	XU X, WU B, XIE L, et al. A novel ship speed and heading estimation approach using radar sequential images[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(10): 1-14. doi: 10.1109/TITS.2023.3340370 URL
[22]	CHO Y, HAN J, KIM J. Efficient COLREG-compliant collision avoidance in multi-ship encounter situations[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(3): 1899-1911. doi: 10.1109/TITS.2020.3029279 URL
[23]	ZHAO L, FU X. A method for correcting the closest point of approach index during vessel encounters based on dimension data from AIS[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(8): 13745-13757. doi: 10.1109/TITS.2021.3127223 URL
[24]	SHI Z, ZHEN R, LIU J. Fuzzy logic-based modeling method for regional multi-ship collision risk assessment considering impacts of ship crossing angle and navigational environment[J]. Ocean Engineering, 2022, 259: 111847. doi: 10.1016/j.oceaneng.2022.111847 URL
[25]	XU X, WU B, et al. Integration of radar sequential images and AIS for ship speed and heading estimation under uncertainty[J]. IEEE Transactions on Intelligent Transportation Systems, 2024, 25(6): 5688-5702. doi: 10.1109/TITS.2023.3338293 URL
[26]	ZHANG Y, XIAO Y, TENG F, et al. Distributed energy management method with EEOI limitation for the ship-integrated energy system[J]. IEEE Systems Journal, 2024, 18(2): 1332-1343. doi: 10.1109/JSYST.2024.3361709 URL
[27]	XIE P M. GUERRERO J M, TAN S, et al. Optimization-based power and energy management system in shipboard microgrid: A review[J]. IEEE Systems Journal, 2022, 16(1): 578-590. doi: 10.1109/JSYST.2020.3047673 URL
[28]	QIU J, TAO Y, LAI S, et al. Pricing strategy of cold ironing services for all-electric ships based on carbon integrated electricity price[J]. IEEE Transactions on Sustainable Energy, 2022, 13(3): 1553-1565. doi: 10.1109/TSTE.2022.3157645 URL
[29]	YU T Y, ISLAM M M, WANG J, et al. Robust optimization in energy management under RESs uncertainties through BESS integration[C]// 2023 5th International Conference on Electrical Engineering and Control Technologies (CEECT). Shanghai, China: IEEE, 2023: 85-91.
[30]	徐玉琴, 方楠. 基于分段线性化与改进二阶锥松弛的电-气互联系统多目标优化调度[J]. 电工技术学报, 2022, 37(11): 2800-2812.
	XU Yuqin, FANG Nan. Multi objective optimal scheduling of integrated electricity-gas system based on piecewise linearization and improved second order cone relaxation[J]. Transactions of China Electrotechnical Society, 2022, 37(11): 2800-2812.

k	坐标/ n mile	硬性时间窗/h	k	坐标/ n mile	硬性时间窗/h
2	(108,55)	[0,20]	6	(60,14)	[0,5]
3	(64,131)	[0,9]	7	(-9,90)	[0,9]
4	(21,73)	[0,5]	8	(-53,130)	[0,9]
5	(132,89)	[0,18]	9	(-84,92)	[0,15]

n	航线	航行距离/n mile	行驶时间/h
1	1→6→3→5→2→1	421.42	18.047 3
2	1→4→7→8→9→1	343.52	15.450 7

单元	型号	a₂, a₁, a₀	P_max/kW	P_min/kW	λ_DG
发电机	1	5.8×10^-5, 0.223, 19	900	180	0.62
	2	5.2×10^-5, 0.215, 15	1 150	250	0.82
	3	5.2×10^-5, 0.215, 15	1 150	250	0.82
	4	5.2×10^-5, 0.200, 15	600	50	0.52
单元	型号	b₂, b₁, b₀	${\mathit{R}}_{\mathrm{D}\mathrm{G}}^{\mathrm{u}\mathrm{p}}$/kW	${\mathit{R}}_{\mathrm{D}\mathrm{G}}^{\mathrm{d}\mathrm{o}\mathrm{w}\mathrm{n}}$/kW	μ_st,μ_sd
发电机	1	3.63, -2 000, 450	300	300	50, 50
	2	3.86, -2 000, 8 383	250	250	60, 60
	3	3.86, -2 000, 8 383	250	250	60, 60
	4	3.00, -650, 450	150	150	30, 30
单元	型号	E_ESS/(kW·h)	S_SOC,max, S_SOC,min	η_ch, η_dis	v_min, v_max/kn
船体	1	2 500	0.95, 0.2	0.95, 0.88	0, 30

航线	行驶角度/(°)	遭遇角
1→6	13.132 2	θ^t_w-13.132 2°
6→3	88.040 7	θ^t_w-88.040 7°
3→5	-31.701 8	θ^t_w+31.070 8°
5→2	-124.077 2	θ^t_w+124.077 2°
2→1	-153.013 7	θ^t_w+153.013 7°

工况	航线	平均速度/kn	运行时间/h	平均推进功率/kW
a	①:1→6→3	16.62	8	2 258.81
	②:3→5	17.95	4	9 011.22
	③:5→2→1	23.94	8	27 332.78
b	①:1→6→3	19.86	9	5 197.37
	②:3→5	19.98	4	8 930.62
	③:5→2→1	23.26	7	24 519.84