Scenario-Transformation-Based Optimal Sizing of Hybrid Hydrogen-Battery Storage for Multi-Timescale Islanded Microgrids

被引:17
|
作者
Jiang, Sheng [1 ]
Wen, Shuli [1 ]
Zhu, Miao [1 ]
Huang, Yuqing [2 ]
Ye, Huili [1 ]
机构
[1] Shanghai Jiao Tong Univ, Key Lab Control Power Transmiss & Convers, Minist Educ, Shanghai 200240, Peoples R China
[2] Shanghai Marine Equipment Res Inst, Dept Technol Manage, Shanghai 200031, Peoples R China
关键词
Clustering algorithm; hydrogen-battery energy storage; multiple-timescale operation; optimal sizing; scenario transformation; seasonal imbalance; STL decomposition; ENERGY-STORAGE; REPRESENTATIVE DAYS; SYSTEM; OPTIMIZATION;
D O I
10.1109/TSTE.2023.3246592
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The increasing penetration of volatile renewable energy poses a significant challenge for islanded microgrids in maintaining the seasonal power balance on a long-term timescale. To support renewable integration, seasonal energy storage techniques are expected to coordinate with short-term storage systems to compensate for power mismatches on multiple timescales. However, hybrid storage sizing is often hindered by the coupling of different timescales, which will lead to a large number of variables and greater computational complexity. Thus, in this article, a novel optimal sizing framework is proposed for a hybrid hydrogen-battery storage system, considering a year-round time horizon. To ensure reliable planning of hydrogen storage, a "seasonal-trend decomposition based on LOESS (STL)" technique is applied to preserve long-term power fluctuation characteristics during scenario clustering. Moreover, a least-squares-based scenario approximation method is developed to improve the accuracy of the clustering results. On this basis, a scenario-transformation solution method is proposed to avoid a large number of variables due to year-round hourly operation. The case studies verify the advantages and efficiency of the proposed method.
引用
收藏
页码:1784 / 1795
页数:12
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