混合电解槽阵列协同的风光耦合制氢系统双层多目标优化

Bi-Level Multi-Objective Optimization of a Wind-Solar Coupled Hydrogen Production System Based on the Synergy of Hybrid Electrolyzer Arrays

摘要

为解决单一类型电解槽阵列难以兼顾经济性与宽功率波动下的运行灵活性这一问题，提出一种基于混合电解槽阵列协同的风光耦合制氢系统，利用不同电解槽的特性差异实现优势互补，进而建立了系统的双层多目标优化策略。上层利用非支配排序遗传算法进行宏观容量配置多目标寻优；下层建立双层混合整数线性规划模型，其中聚合模型用于快速评估上层配置方案，精细化模型则准确刻画每个电解槽单元的动态运行特性。结果表明：相较于传统的顺序启停与定期轮换策略，所提策略使单位制氢成本分别降低了14.9%和22.0%，显著提升了系统的经济效益；此外，系统表现出良好的长周期运行适应性，在面临季节交替与波动氢气需求时，单位制氢成本的最高季节性增幅控制在11.16%以内；且相较于平稳需求场景，所提策略通过灵活调控进一步使制氢成本下降了3.93%～7.98%，有效克服了长周期波动影响。研究成果可为实现兼顾高效与灵活的可再生能源制氢系统提供可行方案。

Abstract

To address the challenge that single-type electrolyzer arrays struggle to balance economic viability with operational flexibility under wide power fluctuations, a wind-solar coupled hydrogen production system based on the synergy of hybrid electrolyzer arrays is proposed. By leveraging the complementary characteristics of different electrolyzers to obtain complementary benefits, a bi-level multi-objective optimization strategy for the system is established. In the upper level, a non-dominated sorting genetic algorithm is employed to perform multi-objective optimization for macro-level capacity allocation. In the lower level, a bi-level mixed-integer linear programming (MILP) model is formulated, consisting of an aggregation model for the rapid evaluation of upper-level configurations and a refined model to accurately characterize the operational dynamics of each electrolyzer unit. The results show that, the proposed optimization scheme reduces the unit hydrogen production cost by 14.9% relative to conventional sequential start-stop strategies and by 22.0% relative to periodic rotation strategies, significantly enhancing the economic efficiency of the system. Moreover, the system demonstrates excellent long-term operational adaptability. Under seasonal transitions and fluctuating hydrogen demands, the maximum seasonal increase in unit hydrogen production cost is controlled within 11.16%. Furthermore, compared with the steady demand scenario, the proposed strategy further reduces the hydrogen production cost by 3.93%—7.98% through flexible regulation, effectively overcoming the impacts of long-term fluctuations. These findings are intended to provide a feasible solution for achieving both high efficiency and flexibility in renewable energy-based hydrogen production.

关键词

可再生能源制氢 / 混合电解槽阵列 / 风光耦合 / 容量配置 / 双层多目标优化

Key words

renewable energy-based hydrogen production / hybrid electrolyzer arrays / wind-solar coupling / capacity allocation / bi-level multi-objective optimization

参考文献

[1] 李晖，刘栋，姚丹阳 . 面向碳达峰碳中和目标的我国电力系统发展研判[J].中国电机工程学报，2021，41(18)：6245-6258.

[2] Li Hui, Liu Dong, Yao Danyang . Analysis and reflection on the development of power system towards the goal of carbon emission peak and carbon neutrality[J].Proceedings of the CSEE, 2021, 41(18): 6245-6258.

[3] 梁忠豪，王丽芳，李建林 . 基于纳什均衡的光—储耦合制氢系统优化控制方法[J].电力系统自动化，2025，49(3)：125-134.

[4] Liang Zhonghao, Wang Lifang, Li Jianlin . Nash equilibrium based optimal control method for hydrogen production system with photovoltaic—storage coupling[J].Automation of Electric Power Systems, 2025, 49(3): 125-134.

[5] 胡可崴，李浩，王创，等 . 电解水制氢的多物理场建模与监控技术综述[J].电力自动化设备，2023，43(12)：3-13.

[6] Hu Kewai, Li Hao, Wang Chuang, et al. Review on multiphysics modeling and regulation of power—to—hydrogen electrolyzer[J].Electric Power Automation Equipment, 2023, 43(12): 3-13.

[7] 王士博，孔令国，蔡国伟，等 . 电力系统氢储能关键应用技术现状、挑战及展望[J].中国电机工程学报，2023，43(17)：6660-6681.

[8] Wang Shibo, Kong Lingguo, Cai Guowei, et al. Current status, challenges and prospects of key application technologies for hydrogen storage in power system[J].Proceedings of the CSEE, 2023, 43(17): 6660-6681.

[9] Hassan Q, Sameen A Z, Salman H M, et al. Large—scale green hydrogen production via alkaline water electrolysis using solar and wind energy[J].International Journal of Hydrogen Energy, 2023, 48(88): 34299-34315.

[10] Sebbahi S, Assila A, Bleghiti A A, et al. A comprehensive review of recent advances in alkaline water electrolysis for hydrogen production[J].International Journal of Hydrogen Energy, 2024, 82: 583-599.

[11] Kojima H, Nagasawa K S, Todoroki N, et al. Influence of renewable energy power fluctuations on water electrolysis for green hydrogen production[J].International Journal of Hydrogen Energy, 2023, 48(12): 4572-4593.

[12] 林嘉虎 . 离网型风光制氢系统混合电解槽优化运行及容量配置策略研究[D].哈尔滨：东北林业大学，2025.

[13] 华佳楠，于天佑，周荔丹，等 . 基于混合电解槽运行特性的风光制氢系统功率分配策略[J/OL].上海交通大学学报.(2025—11—14)[2025—12—11].https://doi.org/10.16183/j.cnki.jsjtu.2025.183.

[14] Hua Jianan, Yu Tianyou, Zhou Lidan, et al. Power allocation strategy for wind—solar hydrogen production system based on operating characteristics of hybrid electrolyzers[J/OL].Journal of Shanghai Jiaotong University. (2025—11—14)[2025—12—11].https://doi.org/10.16183/j.cnki.jsjtu.2025.183.

[15] 谢金勇，张逸，张亚超，等 . 考虑混合电解槽协同运行的园区级氢能系统优化配置方法[J].电网技术，2025，49(8)：3256-3265.

[16] Xie Jinyong, Zhang Yi, Zhang Yachao, et al. Optimized configuration method of park—level hydrogen energy system for coordinated operation of hybrid electrolyzers[J].Power System Technology, 2025, 49(8): 3256-3265.

[17] 徐衍会，李冠霖 . 基于碱性—质子交换膜混合电解槽的离网型风光耦合制氢系统容量配置优化[J].电力自动化设备，2025，45(4)：1-9.

[18] Xu Yanhui, Li Guanlin . Capacity configuration optimization of off—grid wind—solar coupling hydrogen production system based on alkaline—proton exchange membrane hybrid electrolyzers[J].Electric Power Automation Equipment, 2025, 45(4): 1-9.

[19] Yu Binbin, Fan Guangyao, Sun Kai, et al. Adaptive energy optimization strategy of island renewable power—to—hydrogen system with hybrid electrolyzers structure[J].Energy, 2024, 301: 131508.

[20] Zhou Zheng, Zhang Sen, Zhong Yin, et al. A predictive control method for multi—electrolyzer off—grid hybrid hydrogen production systems with photovoltaic power prediction[J].International Journal of Hydrogen Energy, 2024, 84: 383-393.

[21] 陈朝旭，张亚超，朱蜀，等 . 考虑多电解槽多工况组合运行的电—氢—热综合能源系统优化调度[J].电网技术，2025，49(2)：542-551.

[22] Chen Zhaoxu, Zhang Yachao, Zhu Shu, et al. Optimal scheduling of electricity—hydrogen—heat integrated energy system considering combined operation of multi—electrolyzers under multiple conditions[J].Power System Technology, 2025, 49(2): 542-551.

[23] 宋维山，谢丽蓉，张龙军，等 . 计及电解槽多模式运行制氢策略的微电网双层容量规划[J].智慧电力，2025，53(10)：44-53.

[24] Song Weishan, Xie Lirong, Zhang Longjun, et al. Bi—level capacity planning of microgrid considering multi—mode electrolyzer operation strategy for hydrogen production[J].Smart Power, 2025, 53(10): 44-53.

[25] 沈小军，聂聪颖，吕洪 . 计及电热特性的离网型风电制氢碱性电解槽阵列优化控制策略[J].电工技术学报，2021，36(3)：463-472.

[26] Shen Xiaojun, Nie Congying, Lü Hong . Coordination control strategy of wind power—hydrogen alkaline electrolyzer bank considering electrothermal characteristics[J].Transactions of China Electrotechnical Society, 2021, 36(3): 463-472.

[27] Wang Shibo, Kong Lingguo, Liu Chao, et al. Collaborative operation of renewable energy hydrogen production systems considering balanced utilization and extended lifespan of multi—electrolyzers[J].IEEE Transactions on Sustainable Energy, 2025, 16(4): 3064-3081.

[28] Fang Ruiming, Liang Yin . Control strategy of electrolyzer in a wind—hydrogen system considering the constraints of switching times[J].International Journal of Hydrogen Energy, 2019, 44(46): 25104-25111.

[29] 李建林，孙浩元，梁忠豪 . 考虑混合电解槽阵列协同工作的风光制氢系统容量优化配置[J].电力自动化设备，2025，45(9)：11-19.

[30] Li Jianlin, Sun Haoyuan, Liang Zhonghao . Capacity optimization configuration of wind—solar hydrogen production system considering collaborative operation of hybrid electrolyzer arrays[J].Electric Power Automation Equipment, 2025, 45(9): 11-19.

[31] 李建林，赵文鼎，梁忠豪，等 . 基于混合电解槽制氢系统的功率分配技术[J].电力系统自动化，2024，48(13)：9-18.

[32] Li Jianlin, Zhao Wending, Liang Zhonghao, et al. Power distribution technology based on hybrid—electrolyzer hydrogen production system[J].Automation of Electric Power Systems, 2024, 48(13): 9-18.

[33] 杨紫娟，田雪沁，吴伟丽，等 . 考虑电解槽组合运行的风电—氢能—HCNG耦合网络容量优化配置[J].电力系统自动化，2023，47(12)：76-85.

[34] Yang Zijuan, Tian Xueqin, Wu Weili, et al. Optimal capacity configuration of wind—hydrogen—HCNG coupled network considering combined electrolyzer operation[J].Automation of Electric Power Systems, 2023, 47(12): 76-85.

[35] 郑博，白章，袁宇，等 . 多类型电解协同的风光互补制氢系统与容量优化[J].中国电机工程学报，2022，42(23)：8486-8495.

[36] Zheng Bo, Bai Zhang, Yuan Yu, et al. Hydrogen production system and capacity optimization based on synergistic operation with multi—type electrolyzers under wind—solar power[J].Proceedings of the CSEE, 2022, 42(23): 8486-8495.

[37] 李志伟，赵雨泽，吴培 . 碳交易机制下绿氢蓝氢协调优化对综合能源系统的影响评估[J].太阳能学报，2024，45(10)：37-47.

[38] Li Zhiwei, Zhao Yuze, Wu Pei . Impact assessment of coordinated optimization of green hydrogen and blue hydrogen on integrated energy system under carbon trading mechanism[J].Acta Energiae Solaris Sinica, 2024, 45(10): 37-47.

[39] Kountouris I, Langer L, Bramstoft R, et al. Power—to—X in energy hubs: a Danish case study of renewable fuel production[J].Energy Policy, 2023, 175: 113439.

[40] 张玉敏，张念上，吉兴全，等 . 计及秒级响应特性的混合电解制氢系统功率分配策略[J/OL].电力系统自动化.(2025—07—24)[2025—12—11].https://link.cnki.net/urlid/32.1180.TP.20250724.1306.002.

[41] Zhang Yumin, Zhang Nianshang, Ji Xingquan, et al. Power distribution strategy for hybrid electrolytic hydrogen production systems considering second—level response characteristics[J/OL].Automation of Electric Power Systems. (2025—07—24)[2025—12—11].https://link.cnki.net/urlid/32.1180.TP.20250724.1306.002.

基金资助

国家自然科学基金资助项目(52336009)

国家自然科学基金资助项目(52406177)