考虑氢储能电热优化分配的电热氢多能互补系统容量配置优化

Capacity Configuration Optimization of Electro-thermal Hydrogen Multi-energy Complementary System Considering Electro-thermal Optimal Distribution of Hydrogen Energy Storage

  • 摘要: 氢储能技术兼具清洁与热电联供等优点,有望成为新型储能系统的重要支撑。然而,传统氢储能单元的热电联供模式存在两大局限:一是热电耦合性强,降低了供能灵活性;二是为实现高效率,需投入高昂的氢燃料电池余热回收成本。针对上述问题,提出一种考虑天然气管网掺氢和含基于燃氢燃气轮机的氢储能并网型多能互补系统优化配置方法。结合燃氢燃气轮机的工作特性,通过天然气管网掺氢比的动态调节来优化氢储能单元的电热分配,实现氢能的高效利用和容量的合理配置。首先,建立包含电解槽、储氢罐、燃氢燃气轮机和燃气锅炉的并网型多能互补系统的双层优化配置模型,上层模型以系统等年值综合成本最小为优化目标,下层模型以系统年运行成本最小为优化目标;然后,采用混沌粒子群算法和Cplex求解器对双层优化配置模型求解。算例结果验证了所建模型的合理性和有效性,该模型能为含氢储能的多能互补系统容量配置提供参考。

     

    Abstract: Hydrogen energy storage has numerous advantages, such as cleanliness and combined heat and power (CHP), making it a potential cornerstone technology for new energy storage. However, traditional CHP units in hydrogen energy storage systems require careful consideration of the high costs associated with recovering excess heat from hydrogen fuel cells to achieve high efficiency. Moreover, the nature of heat and power coupling results in a limited flexibility in their energy supply flexibility. To address these issues, we propose an optimization method for configuring a grid-connected multi-energy complementary system based on hydrogen blending in natural gas pipelines and hydrogen energy storage with hydrogen-fired gas turbines. By leveraging the operational characteristics of hydrogen-fired gas turbines, the dynamic adjustment of hydrogen blending ratios in natural gas pipelines is capable of optimizing the electric and thermal distribution of hydrogen energy units, thereby achieving efficient utilization of hydrogen energy and a rational capacity configuration. Firstly, a dual-layer optimization configuration model for the grid-connected multi-energy complementary system is developed, including electrolyzer units, hydrogen storage tanks, hydrogen-fired gas turbines, and gas boilers. The upper-layer model is designed to minimize the system’s comprehensive annual cost, while the lower-layer model focuses on minimizing the system’s annual operating cost. Subsequently, the chaotic particle swarm algorithm and the Cplex solver are employed to solve the dual-layer optimization configuration model. Case study results confirm the rationality and effectiveness of the proposed model, providing a reference for capacity configuration in multi-energy complementary systems incorporating hydrogen energy storage.

     

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