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
相关论文
共 50 条
  • [1] Multi-Timescale Power Management for Islanded Microgrids Including Storage and Demand Response
    Pourmousavi, S. Ali
    Nehrir, M. Hashem
    Sharma, Ratnesh K.
    IEEE TRANSACTIONS ON SMART GRID, 2015, 6 (03) : 1185 - 1195
  • [2] Optimal Sizing of Electricity-hydrogen Integrated Energy System Considering Multi-timescale Operation of Hydrogen Storage System
    考虑氢能长短周期储能特性的电氢综合能源系统容量配置方法
    Xia, Yanghong (royxiayh@126.com), 2025, 49 (01): : 12 - 21
  • [3] Integrated model for optimal energy management and demand response of microgrids considering hybrid hydrogen-battery storage systems
    Yousri, Dalia
    Farag, Hany E. Z.
    Zeineldin, Hatem
    El-Saadany, Ehab F.
    ENERGY CONVERSION AND MANAGEMENT, 2023, 280
  • [4] Optimal Multi-Timescale Scheduling of Integrated Energy Systems with Hybrid Energy Storage System Based on Lyapunov Optimization
    Yehui Ma
    Dong Han
    Zhuoxin Lu
    Journal of Beijing Institute of Technology, 2024, 33 (05) : 465 - 480
  • [5] Optimal Sizing of Battery Energy Storage Systems for Small Modular Reactor based Microgrids
    Liu, Xuebo
    Ross, Molly
    Bindra, Hitesh
    Wu, Hongyu
    2021 IEEE KANSAS POWER AND ENERGY CONFERENCE (KPEC), 2021,
  • [6] Multi-Timescale Coordinated Control With Optimal Network Reconfiguration Using Battery Storage System in Smart Distribution Grids
    Zafar, Raheel
    Pota, Hemanshu R.
    IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2023, 14 (04) : 2338 - 2350
  • [7] A Hybrid Method for Optimal Siting and Sizing of Battery Energy Storage Systems in Unbalanced Low Voltage Microgrids
    Carpinelli, Guido
    Mottola, Fabio
    Proto, Daniela
    Russo, Angela
    Varilone, Pietro
    APPLIED SCIENCES-BASEL, 2018, 8 (03):
  • [8] Multi-stage and multi-timescale optimal energy management for hydrogen-based integrated energy systems
    Fang, Xiaolun
    Dong, Wei
    Wang, Yubin
    Yang, Qiang
    ENERGY, 2024, 286
  • [9] A resilient and intelligent multi-objective energy management for a hydrogen-battery hybrid energy storage system based on MFO technique
    Elkholy, M. H.
    Senjyu, Tomonobu
    Metwally, Hamid
    Farahat, M. A.
    Irshad, Ahmad Shah
    Hemeida, Ashraf M.
    Lotfy, Mohammed Elsayed
    RENEWABLE ENERGY, 2024, 222
  • [10] Multi-timescale optimal scheduling of microgrids for generating new energy output scenarios based on correction error sampling intervals
    Wang, Ruimiao
    Fan, Xiaowei
    Yang, Haifeng
    Dong, Guangde
    Yang, Yi
    Wang, Jingang
    IET SCIENCE MEASUREMENT & TECHNOLOGY, 2024, 18 (09) : 598 - 612