西安交通大学绿色氢电全国重点实验室,710049,西安
作者简介:王世杰(2001—),男,硕士生;
陈玉彬(通信作者),男,教授,博士生导师。
收稿:2026-04-10,
网络首发:2026-05-13,
纸质出版:2026-09-10
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王世杰, 胡书瑞, 程大运, 等. 采用多状态柔性合成的离网型风光氢氨系统两阶段分布鲁棒调度[J]. 西安交通大学学报,2026,60 (9):85-96. https://doi.org/10.7652/xjtuxb202609009.
WANG Shijie, HU Shurui, CHENG Dayun, et al. Two-Stage Distributionally Robust Scheduling of an Off-Grid Wind-Solar-Hydrogen-Ammonia System with Multi-State Flexible Synthesis[J]. Journal of Xi'an Jiaotong University,2026,60 (9):85-96. https://doi.org/10.7652/xjtuxb202609009.
王世杰, 胡书瑞, 程大运, 等. 采用多状态柔性合成的离网型风光氢氨系统两阶段分布鲁棒调度[J]. 西安交通大学学报,2026,60 (9):85-96. https://doi.org/10.7652/xjtuxb202609009. DOI:
WANG Shijie, HU Shurui, CHENG Dayun, et al. Two-Stage Distributionally Robust Scheduling of an Off-Grid Wind-Solar-Hydrogen-Ammonia System with Multi-State Flexible Synthesis[J]. Journal of Xi'an Jiaotong University,2026,60 (9):85-96. https://doi.org/10.7652/xjtuxb202609009. DOI:
针对离网型风光氢氨系统中风光出力波动性与化工生产稳定性的核心矛盾,构建考虑多状态柔性合成的两阶段分布鲁棒优化调度模型。基于电解槽启停特性与合成氨设备多段爬坡机制,建立混合整数线性规划精细化模型,提升系统应对风光出力波动的运行灵活性;耦合燃机掺氢、氨裂解与氨燃料电池单元构建电-氢-氨双向能量转换路径,结合多元储能与氢、氨需求响应机制,强化系统调节能力与新能源消纳水平;搭建数据驱动的两阶段分布鲁棒优化框架,建立风光出力不确定集及极端场景概率分布置信集,日前优化确定机组运行状态与出力计划,日内滚动调整极端场景最恶劣分布下的机组出力,采用非精确列与约束生成算法迭代求解,降低模型保守性并快速逼近最优调度策略。多场景对比仿真验证结果表明:所提模型日内调整成本仅为传统线性调度模型的49.74%,新能源消纳率达97.74%,在保障离网系统氢、氨稳定生产的前提下实现了最优经济调度。
To address the core contradiction between fluctuations in wind and solar power output and the stability of chemical production in an off-grid wind-solar-hydrogen-ammonia system
a two-stage distributionally robust optimization scheduling model considering multi-state flexible synthesis is constructed.Based on the start-stop characteristics of electrolyzers and the multistage ramping mechanism of ammonia synthesis units
a refined mixed-integer linear programming model is established to improve the operational flexibility of the system in coping with wind and solar power fluctuations.A bidirectional electricity-hydrogen-ammonia energy conversion pathway is constructed by integrating hydrogen-blended gas turbines
ammonia cracking units
and ammonia fuel cells.Combined with multiple energy storage systems and hydrogen and ammonia demand response mechanisms
the system regulation capability and renewable energy accommodation level are enhanced.Furthermore
a data-driven two-stage distributionally robust optimization framework is established
in which an uncertainty set for wind and solar power output and a confidence set for the probability distributions of extreme scenarios are constructed.The unit operating states and output schedules are determined through day-ahead optimization
while the unit outputs under the worst-case distribution of extreme scenarios are adj usted through intraday rolling optimization.The model is solved iteratively using the inexact column-and-constraint generation algorithm to reduce model conservatism and rapidly approach the optimal scheduling strategy.It is demonstrated through multi-scenario comparative simulations that
compared with the traditional linear scheduling model
the intraday adj ustment cost of the proposed model is only 49.74% of that of the traditional model
and the renewable energy accommodation rate reaches 97.74%.Optimal economic scheduling is achieved while stable hydrogen and ammonia production in the off-grid system is ensured.
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