考虑电解槽寿命的离网风光互补制氢系统双层嵌套配置优化策略研究OA
Research on two-layer nested configuration optimization strategy for off-grid wind-solar complementary hydrogen production system considering electrolyzer lifetime
为精准匹配离网风光互补制氢系统当地资源并降低全生命周期成本,提出了一种容量配置优化方法.通过构建光伏、风机及蓄电池的能效模型,特别是电解槽寿命模型,动态量化制氢功率对设备寿命的影响,突破传统固定寿命假设的局限.以平准化制氢成本(LCOH)最小化为目标,设计了一种双层嵌套优化框架:内层采用基于规则的能量管理策略实现功率分配,外层则运用蚁群优化算法进行系统容量参数寻优.选取西藏八宿和青海格尔木的实际风光资源数据进行验证,结果表明,所提策略较传统方法可显著降低LCOH,有效提升系统经济性,为离网制氢系统的工程应用提供理论依据.
To accurately match local resources of off-grid wind-solar complementary hydrogen production systems and reduce life cycle cost,a capacity configuration optimization method was proposed.Energy efficiency models of photovoltaic units,wind turbines,and batteries were established,and particularly,an electrolyzer lifetime model was developed to dynamically quantify the influence of hydrogen production power on equipment lifetime,thereby overcoming the limitations of the traditional fixed-lifetime assumption.With the objective of minimizing levelized cost of hydrogen(LCOH),a two-layer nested optimization framework was designed.The inner layer adopted a rule-based energy management method to realize power distribution,while the outer layer applied the ant colony optimization algorithm to optimize the system capacity parameters.Actual wind and solar resource data from Baxoi,Tibet and Golmud,Qinghai were selected for validation.The results showed that the proposed strategy significantly reduced the LCOH and effectively improved the economic performance of the system compared with traditional methods,thus providing a theoretical basis for the engineering application of off-grid hydrogen production systems.
孙浩然;林光伟;汤纪飞;欧阳彦超;王志敏;祝乔;杨锦
东方电气集团东方锅炉股份有限公司,成都 611731西南交通大学 机械工程学院,成都 610031西南交通大学 机械工程学院,成都 610031东方电气集团东方锅炉股份有限公司,成都 611731东方电气集团东方锅炉股份有限公司,成都 611731西南交通大学 机械工程学院,成都 610031东方电气集团东方锅炉股份有限公司,成都 611731
能源科技
电解槽离网风光互补制氢系统配置优化双层嵌套能量管理蚁群优化算法
electrolyzeroff-grid wind-solar complementary hydrogen production systemconfiguration optimizationtwo-layer nested strategyenergy managementant colony optimization algorithm
《综合智慧能源》 2026 (5)
56-63,8
四川省科技计划项目(2024ZDZX0034) Science and Technology Program Project of Sichuan Province(2024ZDZX0034)
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