面向低碳社区电氢储能系统的跨季节递阶优化调度

陈传笑; 于艾清; 桑一岩

doi:10.19799/j.cnki.2095-4239.2026.0432

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面向低碳社区电氢储能系统的跨季节递阶优化调度

储能系统与工程 | 更新时间：2026-10-22

- 面向低碳社区电氢储能系统的跨季节递阶优化调度
- Hierarchical optimal scheduling method for electric-hydrogen hybrid energy storage in low-carbon communities considering cross-seasonal energy shifting
- 储能科学与技术 2026年15卷第10期页码：4004-4024
- 作者机构：
  
  上海电力大学电气工程学部，上海 200090
- 作者简介：
  
  陈传笑（2000—），男，硕士研究生，研究方向为电氢混合储能系统运行优化，E-mail：1731408973@qq.com；
  于艾清，副教授，研究方向为新型电力系统规划、智能算法，E-mail：yuaiqing@shiep.edu.cn。
- 基金信息：
  
  国家自然科学基金项目(52507123)
- DOI：10.19799/j.cnki.2095-4239.2026.0432
  中图分类号： TM 911
- 收稿：2026-05-18，
  
  修回：2026-08-20，
  
  纸质出版：2026-10-28
- 稿件说明：
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陈传笑, 于艾清, 桑一岩. 面向低碳社区电氢储能系统的跨季节递阶优化调度[J]. 储能科学与技术, 2026, 15(10): 4004-4024.

CHEN Chuanxiao, YU Aiqing, SANG Yiyan. Hierarchical optimal scheduling method for electric-hydrogen hybrid energy storage in low-carbon communities considering cross-seasonal energy shifting[J]. Energy Storage Science and Technology, 2026, 15(10): 4004-4024.
陈传笑, 于艾清, 桑一岩. 面向低碳社区电氢储能系统的跨季节递阶优化调度[J]. 储能科学与技术, 2026, 15(10): 4004-4024. DOI： 10.19799/j.cnki.2095-4239.2026.0432.

CHEN Chuanxiao, YU Aiqing, SANG Yiyan. Hierarchical optimal scheduling method for electric-hydrogen hybrid energy storage in low-carbon communities considering cross-seasonal energy shifting[J]. Energy Storage Science and Technology, 2026, 15(10): 4004-4024. DOI： 10.19799/j.cnki.2095-4239.2026.0432.

摘要

针对高比例光伏低碳社区中短时功率波动与跨季节能量错配并存、单一电化学储能难以兼顾长周期能量搬移和小时级快速调节的问题，提出一种面向跨季节能量搬移的电氢混合储能系统递阶优化调度方法。该方法以跨季节储氢目标的逐级落地为主线，构建“年度目标生成、月度风险缓冲、日内滚动执行”的三层调度框架，使长期储氢目标、中期周度计划和小时级控制量在同一闭环中协调更新。年度层采用马尔可夫决策过程生成季节性储氢目标，刻画当前储氢状态、电池荷电状态和寿命损耗对后续运行成本的影响；月度层建立计及光伏和负荷扰动的两阶段随机规划模型，将年度储氢目标转化为具有安全裕度的周度计划；日内层采用模型预测控制滚动优化，并结合净负荷快慢分量分解和非线性电池退化成本，引导电池承担短时波动补偿、氢储能承担跨月和跨季节能量搬移。基于某低碳社区全年8760 h源荷数据的算例表明，与无氢储能模型相比，电氢混合储能模型年度运行成本降低44.07%，缺供量降低97.87%；与年度-日内两层结构相比，三层递阶模型使典型周储氢跟踪误差均方根值由36.31 MWh降至27.37 MWh，降低24.6%；引入非线性电池退化成本后，超过单时段较大放电惩罚阈值的放电时段比例由50.92%降至1.50%，电池年吞吐量由1626.44 MWh降至432.90 MWh，等效循环次数由271.07次降至72.15次；在8组外部扰动场景下，月度两阶段随机规划以平均成本仅增加0.13%为代价，使平均缺供量降低9.5%，平均实际最低储氢量提高12.9 MWh。结果表明，所提方法能够在高比例光伏低碳社区中实现氢储能长周期能量搬移、电池短时调节和不确定性风险缓冲的协调统一。

Abstract

To address the coexistence of short-term power fluctuations and cross-seasonal energy mismatches in low-carbon communities with high photovoltaic penetration

this study proposes a hierarchical optimal scheduling method for an electric-hydrogen hybrid energy storage system. This method progressively implements seasonal hydrogen-storage targets

linking annual target generation

monthly risk buffering

and intraday rolling execution within a closed-loop scheduling framework. At the annual level

a Markov decision process is formulated to generate seasonal hydrogen-storage targets while accounting for the impacts of hydrogen inventory

battery state of charge

and accumulated degradation on future operating costs. At the monthly level

a two-stage stochastic programming model incorporating photovoltaic and load disturbances is developed to translate annual hydrogen targets into weekly plans with security margins. At the intraday level

model predictive control is adopted for rolling optimization

while fast/slow net-load decomposition and a nonlinear battery-degradation cost are incorporated to guide batteries in compensating for short-term fluctuations and in hydrogen storage during monthly and seasonal energy shifting. Case studies based on 8760 h source-load data from a low-carbon community show that

under the given device capacities

the electric-hydrogen hybrid storage model reduces the annual operating cost and power shortage by 44.07% and 97.87%

respectively

compared with a benchmark without hydrogen storage. Compared with an annual-intraday two-level structure

the proposed three-level model reduces the root-mean-square error in hydrogen-inventory tracking over a typical week from 36.31 to 27.37 MWh. Incorporating the nonlinear degradation cost reduces the proportion of discharging periods exceeding the single-period high-discharge penalty threshold from 50.92% to 1.50%

lowers the annual battery throughput from 1626.44 to 432.90 MWh

and decreases equivalent full cycles from 271.07 to 72.15. Across eight external-disturbance scenarios

the monthly stochastic layer reduces the average power shortage by 9.5% and increases the average actual minimum hydrogen inventory by 12.9 MWh while only increasing the average cost by 0.13%. The results demonstrate that the proposed method effectively coordinates long-duration hydrogen shifting

short-term battery regulation

and uncertainty-risk buffering in low-carbon-community energy systems.

关键词

Keywords

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