Two-Stage Distributionally Robust Scheduling for Multi-State Flexible Synthesis in Off-Grid Wind-Solar-Hydrogen-Ammonia Systems

WANG Shijie; HU Shurui; CHENG Dayun; LI Mingtao; CHEN Yubin

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Two-Stage Distributionally Robust Scheduling for Multi-State Flexible Synthesis in Off-Grid Wind-Solar-Hydrogen-Ammonia Systems

更新时间：2026-07-29

- Two-Stage Distributionally Robust Scheduling for Multi-State Flexible Synthesis in Off-Grid Wind-Solar-Hydrogen-Ammonia Systems
- JOURNAL OF XI’AN JIAOTONG UNIVERSITY (2026)
- 作者机构：
  
  西安交通大学绿色氢电全国重点实验室，710049，陕西西安
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM732
- Received：10 December 2025，
  
  Revised：2026-03-18，
  
  Accepted：12 April 2026，
- 稿件说明：
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WANG Shijie, HU Shurui, CHENG Dayun, et al. Two-Stage Distributionally Robust Scheduling for Multi-State Flexible Synthesis in Off-Grid Wind-Solar-Hydrogen-Ammonia Systems[J/OL]. JOURNAL OF XI’AN JIAOTONG UNIVERSITY, 2026.
DOI：

WANG Shijie, HU Shurui, CHENG Dayun, et al. Two-Stage Distributionally Robust Scheduling for Multi-State Flexible Synthesis in Off-Grid Wind-Solar-Hydrogen-Ammonia Systems[J/OL]. JOURNAL OF XI’AN JIAOTONG UNIVERSITY, 2026. DOI：

摘要

针对离网型风光氢氨耦合系统中风光波动性与化工生产稳定性的矛盾，本文提出一种考虑多状态柔性合成的两阶段分布鲁棒优化调度模型。首先，通过分析实际生产中电解槽启停特性与合成氨设备多段爬坡机制，构建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；其次，耦合燃机掺氢、氨裂解与氨燃料电池构建电氢氨双向转换路径，结合多元储能与氢、氨需求响应机制，增强系统调节能力与新能源消纳水平。最后，构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，日前优化机组状态与出力计划，日内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，在降低模型保守性的同时快速逼近最优策略。结果表明，所提模型依托精细化建模适配风光波动性，结合分布鲁棒优化基于场景样本的求解策略适配风光不确定性，日内调整成本仅为传统线性模型49.74%，新能源消纳率达到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。

Abstract

In order to address the conflict between the volatility of renewable energy and the stability requirements of chemical production in an off-grid wind-solar-hydrogen-ammonia coupled system

this paper proposes a two-stage distributionally robust optimization scheduling model considering multi-state flexible synthesis. Firstly

an analysis was conducted of the start-stop characteristics of electrolyzers and the multi-stage ramp operation mechanism of ammonia synthesis units in practical production

and a refined mixed-integer linear programming model is constructed to improve the system's operational flexibility in responding to the inherent fluctuation characteristics of wind-solar output. Secondly

a bidirectional power-hydrogen-ammonia conversion pathway is constructed by integrating hydrogen-blended gas turbines

ammonia cracking

and ammonia fuel cells

along with multi-energy storage and hydrogen-ammonia demand response mechanisms

which enhances the system's regulation capability and renewable energy accommodation level. Finally

a data-driven two-stage distributionally robust optimisation framework has been developed. This framework is notable for its formulation of the uncertainty set of renewable generation and the confidence set of extreme scenario probability distributions. The day-ahead stage determines unit commitment and dispatch plans

while the intraday stage adjusts unit outputs under the worst-case distribution of extreme scenarios. The model is iteratively solved using the inexact column-and-constraint generation algorithm

which approaches the optimal strategy rapidly while reducing the model conservatism. Case analysis shows that the proposed model adapts to the volatility of wind-solar output by virtue of refined modeling and to the uncertainty of wind-solar output with the scenario sample-based solution strategy of distributionally robust optimization. Its intraday adjustment cost is only 49.74% of the traditional linear model

and the system's renewable energy consumption rate reaches 97.74%

which achieves optimal economic scheduling on the premise of ensuring the stable production of hydrogen and ammonia in the off-grid system.

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