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储能系统技术 储能系统 可靠性分析 ★ 5.0

联合多阶段规划可再生能源、氢储能与氨储能以深度脱碳高比例可再生能源电力系统

Joint Multi-Stage Planning of Renewable Generation, HESS, and AESS for Deeply Decarbonizing Power Systems With High-Penetration Renewables

作者 Zhipeng Yu · Jin Lin · Feng Liu · Jiarong Li · Yingtian Chi · Yonghua Song
期刊 IEEE Transactions on Sustainable Energy
出版日期 2024年12月
技术分类 储能系统技术
技术标签 储能系统 可靠性分析
相关度评分 ★★★★★ 5.0 / 5.0
关键词 可再生能源 氢能储能系统 氨能储能系统 多阶段容量扩展规划 脱碳成本
语言:

中文摘要

针对高比例可再生能源电力系统深度脱碳中面临的跨日间歇性与源荷季节性失衡问题,传统调节能力受限。本文提出引入氢储能系统(HESS)与氨储能系统(AESS)逐步替代火电,构建含碳排放约束的多阶段容量扩展规划模型,采用年际 hourly 数据刻画可再生能源波动特性。结合Dantzig-Wolfe分解的改进列生成法高效求解大规模模型。基于中国实际系统研究表明:所提方法在不同可再生能源渗透率下均能保障高供电可靠性,避免典型场景法在高渗透(≥30%)下的可靠性下降问题;HESS与AESS显著降低脱碳成本,在碳中和目标下对平准化度电成本降幅贡献分别为12.28%和14.59%,实现998元/吨的碳减排平准化成本。

English Abstract

The further decarbonization of power systems with high renewable energy penetration faces the problem of inter-day intermittence of renewable energy sources (RES) and the seasonal imbalance between RES and load demand, due to the limited regulation ability of conventional units such as thermal generation. Regular solutions based on battery energy storage system (BESS) are too costly to be practical. To address issues above, hydrogen energy storage system (HESS) and ammonia energy storage system (AESS) are introduced to gradually replace thermal generation. Specifically, first, HESS and AESS are incorporated into the multi-stage capacity expansion planning (MSCEP) model with carbon emission reduction constraints. Yearly data with hourly time resolution are utilized for each stage to accurately describe the intermittence of RES. Then, an improved column generation (CG) with Dantzig-Wolfe decomposition (DWD) embedded solution approach is used to efficiently solve the large-scale MSCEP model. Finally, a real-life system in China is studied. The results indicate that the proposed method can guarantee high power supply reliability (PSR) under different renewable energy penetration levels, avoiding the low PSR problem that may be caused by the existing typical scenario-based method (TSM) under high penetration ( 30%). Moreover, HESS and AESS are essential to reduce the cost of decarbonization. Especially under the goal of carbon neutrality, the contribution of HESS and AESS in reducing levelized cost of energy (LCOE) reaches 12.28% and 14.59%, respectively, leading to a levelized cost of carbon reduction (LCOCr) of 998 RMB/t.
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SunView 深度解读

该研究对阳光电源PowerTitan储能系统和ST系列储能变流器的长周期储能规划具有重要价值。文章提出的HESS(氢储能)与AESS(氨储能)协同规划方法,为阳光电源拓展季节性储能解决方案提供理论支撑。研究验证的年际hourly数据建模方法可直接应用于iSolarCloud平台的容量配置优化模块,提升高渗透率场景下的系统可靠性预测精度。HESS/AESS与电化学储能的协同调度策略,可指导PowerTitan系统在深度脱碳场景下的多时间尺度能量管理优化,降低LCOE并提升碳减排经济性。多阶段扩展规划模型为阳光电源储能项目全生命周期投资决策提供量化工具。