Application of an intelligent method for hydrogen-based energy hub in multiple energy markets

被引:10
|
作者
Li, Ziyuan [1 ,2 ]
He, Tao [2 ]
Farjam, Hashem [3 ]
机构
[1] Xiamen Inst Technol, Business Sch, Xiamen 361000, Fujian, Peoples R China
[2] Wenzhou Vocat & Tech Coll, Sch Intelligent Mfg, Wenzhou 325000, Zhejiang, Peoples R China
[3] Sun Life Co, EED, Baku, Azerbaijan
关键词
Energy hub; Optimization algorithm; Demand response; Multi -carrier energy; PREDICTIVE CONTROL; ELECTRICITY; FRAMEWORK; SYSTEMS; STORAGE;
D O I
10.1016/j.ijhydene.2023.03.124
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Use of different energy carriers together, known as an energy hub, has been a hot topic of research. The hub manager manages the energy in the hub and supplies the energy demanded by the consumers. Herein, a multi-carrier energy storage system comprising a thermal energy storage system, ice storage system, and hydrogen storage system is considered for a multi-carrier energy system to exploit their economic benefits. The proposed combined cooling, heating and electricity microgrid not only participates in the electricity, gas and heat market to meet the needs of electricity, heating and cooling, but also can use the new hydrogen power technology used in the hydrogen storage system to increase the efficiency of the whole system participate in the market. In addition, a multienergy demand response model is used as a new concept of demand response on electrical and thermal loads, which provides more options for multi-energy end users in energy management policies. To cover the uncertainty of the existence of different energy sources in the used model and the price of electricity, a new method has been used. The LHS sampling is used to develop diverse scenarios, and the backward scenario reduction method is adopted to decrease the number of scenarios. To solve the objective function and optimization, the metaheuristic whale algorithm improved by a local search algorithm is utilized. The main goal is to reduce the operation costs of the multi-energy carrier system. The obtained results show that the hydrogen storage utilization and multi-energy demand response can reduce the system operation cost by 6% for the studied experimental system. Furthermore, as the uncertainty budget increased, the total cost of operations increased by 10%. This is because the level of planning conservatism increases with each increase in the uncertainty budget. (c) 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:36485 / 36499
页数:15
相关论文
共 50 条
  • [31] The role of hydrogen-based power systems in the energy transition of the residential sector
    Maestre, Victor M.
    Ortiz, Alfredo
    Ortiz, Inmaculada
    JOURNAL OF CHEMICAL TECHNOLOGY AND BIOTECHNOLOGY, 2022, 97 (03) : 561 - 574
  • [32] The socio-political aspects of the transition to hydrogen-based energy systems
    Gladstone, E
    HYDROGEN ENERGY PROGRESS XII, VOLS 1-3, 1998, : 223 - 230
  • [33] Overview of light water/hydrogen-based low energy nuclear reactions
    Miley, George H.
    Shrestha, Prajakti J.
    CONDENSED MATTER NUCLEAR SCIENCE, 2006, : 34 - +
  • [34] Green hydrogen-based energy storage in Texas for decarbonization of the electric grid
    Wikramanayake, Enakshi
    Acharya, Palash, V
    Kapner, Mark
    Bahadur, Vaibhav
    2021 13TH ANNUAL IEEE GREEN TECHNOLOGIES CONFERENCE GREENTECH 2021, 2021, : 409 - 415
  • [36] Optimal Scheduling for Energy Hub in Power Markets
    Fan, Huixian
    Chen, Qixin
    Liu, Wentao
    Li, Jialong
    Chen, Yuguo
    2016 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA), 2016, : 127 - 131
  • [37] Optimal coordination of hydrogen-based integrated energy systems with combination of hydrogen and water storage
    Dong, Xiangxiang
    Wu, Jiang
    Xu, Zhanbo
    Liu, Kun
    Guan, Xiaohong
    APPLIED ENERGY, 2022, 308
  • [38] Perspectives on hydrogen-based energy. Part One: Techniques and systems for hydrogen production
    Dreier, T
    Wagner, U
    BRENNSTOFF-WARME-KRAFT, 2000, 52 (12): : 41 - 46
  • [39] Hydrogen-based Energy Storage (IEA-HIA Task 32)
    Craig E. Buckley
    Ping Chen
    Bart A. van Hassel
    Michael Hirscher
    Applied Physics A, 2016, 122
  • [40] Robustness Evaluation of Energy Management Strategies for Hydrogen-based Railway Vehicles
    Olmos, Josu
    Saez-de-Ibarra, Andoni
    Gaztanaga, Haizea
    Lopez, Dimas
    Nieva, Txomin
    Aizpuru, Iosu
    2023 IEEE VEHICLE POWER AND PROPULSION CONFERENCE, VPPC, 2023,