考虑SOC优化设定的电-氢混合储能系统的运行优化

针对含电-氢混合储能的源网荷储系统，为提高新能源的消纳水平并降低系统运行成本，提出了考虑SOC优化设定的电氢混合储能系统的运行优化方法，实现系统的日前实时优化调度。首先提出了大容量储能系统SOC优化设定的方法，以确定储能系统日前的始末SOC优化设定值。随后，基于双延迟深度确定性策略梯度算法，提出了一种日前实时优化调度模型训练方法。结合储能SOC的优化设定值和日前运行数据，建立了源网荷储系统的实时优化调度模型，实现日前和实时综合优化调度。最后，通过算例分析验证了所提运行优化方法的有效性。结果表明，大容量储能系统的SOC优化设定方法可以有效提高系统收益，日前-实时优化调度模型则在日前优化调度的基础上减少了预测误差带来的影响。

Optimal operation of an electro-hydrogen hybrid energy storage system considering SOC optimization setting

To enhance the efficiency of renewable energy utilization and minimize operational costs within the source- grid-load-storage system with electro-hydrogen hybrid energy storage, this paper presents an optimal operation method of electro- hydrogen hybrid energy storage system considering an SOC optimization setting to realize the day-ahead real-time optimal scheduling of the system. First, a method for SOC optimization setting of high-capacity energy storage systems is proposed to determine the day-ahead SOC optimization settings at the start and end of each day for the energy storage system. Subsequently, based on a twin delayed deep deterministic policy gradient algorithm, a day-ahead real-time optimal scheduling model training method is proposed. A real-time model for source-network-load energy storage system is established based on the optimized set points of energy storage SOCs and day-ahead operation data to achieve day-ahead real-time integrated optimal scheduling. Finally, the effectiveness of the proposed method is validated through case study results. The result indicates that the method proves to be efficient in enhancing system revenue, while the day-ahead real-time optimal scheduling model mitigates the impact of prediction errors.