【摘要】 为应对高渗透率可再生能源带来的不确定性，提出一种基于多场景随机优化的含氢综合能源系统协同规划方法。通过耦合电、热、冷、氢、天然气5类能源载体，构建多能互补的综合能源系统架构。基于历史数据，采用改进的K-means聚类算法生成数据驱动的不确定性场景，并利用线性化技巧将原模型高效求解，优化系统容量配置与运行策略。算例分析表明，所提方法兼顾经济性与鲁棒性，且在提升可再生能源消纳的同时减少系统碳排放。更多还原

【Abstract】 To address uncertainties from high-penetration renewable energy, this paper proposes a collaborative planning method for hydrogen-integrated energy systems, based on multi-scenario stochastic optimization.The framework couples five energy carriers: electricity, heat, cooling, hydrogen, and natural gas, to establish a multi-energy complementary system.Based on historical data, an improved K-means clustering algorithm is used to generate data-driven uncertainty scenarios, and linearization techniques are employed to efficiently solve the original model, optimizing system capacity configuration and operational strategies.Case study results demonstrate that the proposed method achieves a balance between economy and robustness, while improving renewable energy utilization and reducing carbon emissions.更多还原