Hybrid energy storage sizing in energy hubs: A continuous spectrum splitting approach

被引:3
作者
Feng, Songjie [1 ]
Wei, Wei [1 ]
机构
[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
关键词
Hydrogen storage; Battery storage; Capacity sizing; Discrete Fourier transformation; Energy hub; SYSTEM; WIND; OPTIMIZATION; ELECTRICITY; PENETRATION;
D O I
10.1016/j.energy.2024.131504
中图分类号
O414.1 [热力学];
学科分类号
摘要
Renewable powered energy hub is a promising way to realize efficient use of renewable resources through multi -energy integration. To cope with the fluctuation of renewable power at different timescales, longterm and short-term energy storage devices are essential. This paper proposes a frequency -domain approach to determine the appropriate capacities of hydrogen and battery energy storage units in an electricity- hydrogen-heat integrated energy hub. The net demand is mapped to the frequency domain via discrete Fourier transformation (DFT). A continuous spectrum splitting method is developed to allocate the frequency components among generator, hydrogen storage and battery storage. Compared with the time -domain method, it makes better use of the spectral characteristics of the year-round data, leading to robust sizing results without complex modeling of uncertainty. In contrast to the existing cut-off frequency method which assigns highfrequency components to battery storage and low -frequency components to generators according to a cut-off frequency, the proposed framework allows a single spectrum component to be allocated to multiple system devices, which not only makes the optimization model convex but also improves optimality. In addition, the spectrum clustering process further reduces the number of core variables and the computational efficiency is high. The rationality of the sizing results is verified through online operation, where the proposed method achieves an average of 1.93% total load shedding rate compared with 4.42% of the time -domain method, verifying the operation reliability under uncertainty. While fully utilizing the spectrum characteristics, the investment cost is about 22% less than the cut-off frequency result.
引用
收藏
页数:12
相关论文
共 38 条
[1]   Robust self-scheduling of a price-maker energy storage facility in the New York electricity market [J].
Barbry, Adrien ;
Anjos, Miguel F. ;
Delage, Erick ;
Schell, Kristen R. .
ENERGY ECONOMICS, 2019, 78 :629-646
[2]   Capacity Planning of Energy Hub in Multi-Carrier Energy Networks: A Data-Driven Robust Stochastic Programming Approach [J].
Cao, Yang ;
Wei, Wei ;
Wang, Jianhui ;
Mei, Shengwei ;
Shafie-khah, Miadreza ;
Catalao, Joao P. S. .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2020, 11 (01) :3-14
[3]   Progress in electrical energy storage system: A critical review [J].
Chen, Haisheng ;
Cong, Thang Ngoc ;
Yang, Wei ;
Tan, Chunqing ;
Li, Yongliang ;
Ding, Yulong .
PROGRESS IN NATURAL SCIENCE-MATERIALS INTERNATIONAL, 2009, 19 (03) :291-312
[4]   Optimization and integration of hybrid renewable energy hydrogen fuel cell energy systems - A critical review [J].
Eriksson, E. L. V. ;
Gray, E. MacA. .
APPLIED ENERGY, 2017, 202 :348-364
[5]   Understanding of Low-Porosity Sulfur Electrode for High-Energy Lithium-Sulfur Batteries [J].
Fu, Yucheng ;
Singh, Rajesh K. ;
Feng, Shuo ;
Liu, Jun ;
Xiao, Jie ;
Bao, Jie ;
Xu, Zhijie ;
Lu, Dongping .
ADVANCED ENERGY MATERIALS, 2023, 13 (13)
[6]   Optimal planning and operation of multi-carrier networked microgrids considering multi-energy hubs in distribution networks [J].
Ghanbari, Ali ;
Karimi, Hamid ;
Jadid, Shahram .
ENERGY, 2020, 204 (204)
[7]   Hybrid energy storage sizing based on discrete Fourier transform and particle swarm optimization for microgrid applications [J].
Hajiaghasi, Salman ;
Hosseini Ahmadi, Mohammad Milad ;
Goleij, Pedram ;
Salemnia, Ahmad ;
Hamzeh, Mohsen .
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2021, 31 (12)
[8]   Robust Co-Optimization Planning of Interdependent Electricity and Natural Gas Systems With a Joint N-1 and Probabilistic Reliability Criterion [J].
He, Chuan ;
Wu, Lei ;
Liu, Tianqi ;
Bie, Zhaohong .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (02) :2140-2154
[9]   Energy storage system optimization based on a multi-time scale decomposition-coordination algorithm for wind-ESS systems [J].
Hou, Tingting ;
Fang, Rengcun ;
Yang, Dongjun ;
Zhang, Wei ;
Tang, Jinrui .
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2022, 49
[10]   Capabilities of compressed air energy storage in the economic design of renewable off-grid system to supply electricity and heat costumers and smart charging-based electric vehicles [J].
Khalafian, Farshad ;
Iliaee, Nahal ;
Diakina, Ekaterina ;
Parsa, Peyman ;
Alhaider, Mohammed M. ;
Masali, Milad Hadizadeh ;
Pirouzi, Sasan ;
Zhu, Min .
JOURNAL OF ENERGY STORAGE, 2024, 78