IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v283y2023ics0360544223024003.html
   My bibliography  Save this article

Multi-timescale rolling optimization dispatch method for integrated energy system with hybrid energy storage system

Author

Listed:
  • Shen, Weijie
  • Zeng, Bo
  • Zeng, Ming

Abstract

Integrated energy system is an important approach to promote large-scale utilization of renewable energy. Under the context of energy market reformation and technology advancement, the economic operation of integrated energy system confronts new challenges, in terms of multiple uncertainties, multi-timescale characteristics of heterogeneous energy, and coordinated operation of hybrid energy storage system. To this end, this paper investigates the multi-timescale rolling optimization of integrated energy system with hybrid energy storage system considering the above challenges. Firstly, a basic framework of an integrated energy system with hybrid energy storage system (consisting of battery and hydrogen storage) is proposed, and the typical devices are modeled in detail. Secondly, the parameters and variables are divided into fast/slow timescale according to dispatch needs, and the multi-timescale problem of heterogeneous energy and the coordinated operation of the hybrid energy storage system can be solved simultaneously through two-stage optimization. Thirdly, the dispatch model is incorporated into the framework of model predictive control, the uncertainty of price, renewable energy and load can be effectively handled. Finally, a case study is conducted using an industrial park in the southern coastal region of China, the comparison with the rule-based method shows 60.65% reduction in the operating cost of hybrid energy storage system, the comparison with robust optimization shows 7.01% reduction in the total cost of the system, thus the feasibility and effectiveness of the proposed method are verified.

Suggested Citation

  • Shen, Weijie & Zeng, Bo & Zeng, Ming, 2023. "Multi-timescale rolling optimization dispatch method for integrated energy system with hybrid energy storage system," Energy, Elsevier, vol. 283(C).
  • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223024003
    DOI: 10.1016/j.energy.2023.129006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223024003
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2023.129006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Elkazaz, Mahmoud & Sumner, Mark & Naghiyev, Eldar & Pholboon, Seksak & Davies, Richard & Thomas, David, 2020. "A hierarchical two-stage energy management for a home microgrid using model predictive and real-time controllers," Applied Energy, Elsevier, vol. 269(C).
    2. Javed, Muhammad Shahzad & Zhong, Dan & Ma, Tao & Song, Aotian & Ahmed, Salman, 2020. "Hybrid pumped hydro and battery storage for renewable energy based power supply system," Applied Energy, Elsevier, vol. 257(C).
    3. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2022. "Economic model predictive control of integrated energy systems: A multi-time-scale framework," Applied Energy, Elsevier, vol. 328(C).
    4. Liu, Chunming & Wang, Chunling & Yin, Yujun & Yang, Peihong & Jiang, Hui, 2022. "Bi-level dispatch and control strategy based on model predictive control for community integrated energy system considering dynamic response performance," Applied Energy, Elsevier, vol. 310(C).
    5. van der Meer, Dennis & Wang, Guang Chao & Munkhammar, Joakim, 2021. "An alternative optimal strategy for stochastic model predictive control of a residential battery energy management system with solar photovoltaic," Applied Energy, Elsevier, vol. 283(C).
    6. Wang, Huaqing & Xie, Zhuoshi & Pu, Lei & Ren, Zhongrui & Zhang, Yaoyu & Tan, Zhongfu, 2022. "Energy management strategy of hybrid energy storage based on Pareto optimality," Applied Energy, Elsevier, vol. 327(C).
    7. Huang, Chunjun & Zong, Yi & You, Shi & Træholt, Chresten & Zheng, Yi & Wang, Jiawei & Zheng, Zixuan & Xiao, Xianyong, 2023. "Economic and resilient operation of hydrogen-based microgrids: An improved MPC-based optimal scheduling scheme considering security constraints of hydrogen facilities," Applied Energy, Elsevier, vol. 335(C).
    8. Sultana, W. Razia & Sahoo, Sarat Kumar & Sukchai, Sukruedee & Yamuna, S. & Venkatesh, D., 2017. "A review on state of art development of model predictive control for renewable energy applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 391-406.
    9. Parisio, Alessandra & Rikos, Evangelos & Tzamalis, George & Glielmo, Luigi, 2014. "Use of model predictive control for experimental microgrid optimization," Applied Energy, Elsevier, vol. 115(C), pages 37-46.
    10. Tobajas, Javier & Garcia-Torres, Felix & Roncero-Sánchez, Pedro & Vázquez, Javier & Bellatreche, Ladjel & Nieto, Emilio, 2022. "Resilience-oriented schedule of microgrids with hybrid energy storage system using model predictive control," Applied Energy, Elsevier, vol. 306(PB).
    11. Ahmad, Tanveer & Zhang, Dongdong, 2022. "A data-driven deep sequence-to-sequence long-short memory method along with a gated recurrent neural network for wind power forecasting," Energy, Elsevier, vol. 239(PB).
    12. Le, Tay Son & Nguyen, Tuan Ngoc & Bui, Dac-Khuong & Ngo, Tuan Duc, 2023. "Optimal sizing of renewable energy storage: A techno-economic analysis of hydrogen, battery and hybrid systems considering degradation and seasonal storage," Applied Energy, Elsevier, vol. 336(C).
    13. Xie, Shanshan & He, Hongwen & Peng, Jiankun, 2017. "An energy management strategy based on stochastic model predictive control for plug-in hybrid electric buses," Applied Energy, Elsevier, vol. 196(C), pages 279-288.
    14. Li, Jiale & Yang, Bo & Huang, Jianxiang & Guo, Zhengxun & Wang, Jingbo & Zhang, Rui & Hu, Yuanweiji & Shu, Hongchun & Chen, Yixuan & Yan, Yunfeng, 2023. "Optimal planning of Electricity–Hydrogen hybrid energy storage system considering demand response in active distribution network," Energy, Elsevier, vol. 273(C).
    15. Dong, Xing & Zhang, Chenghui & Sun, Bo, 2022. "Optimization strategy based on robust model predictive control for RES-CCHP system under multiple uncertainties," Applied Energy, Elsevier, vol. 325(C).
    16. Kneiske, T.M. & Niedermeyer, F. & Boelling, C., 2019. "Testing a model predictive control algorithm for a PV-CHP hybrid system on a laboratory test-bench," Applied Energy, Elsevier, vol. 242(C), pages 121-137.
    17. Li, Bei & Miao, Hongzhi & Li, Jiangchen, 2021. "Multiple hydrogen-based hybrid storage systems operation for microgrids: A combined TOPSIS and model predictive control methodology," Applied Energy, Elsevier, vol. 283(C).
    18. Lv, Chaoxian & Yu, Hao & Li, Peng & Wang, Chengshan & Xu, Xiandong & Li, Shuquan & Wu, Jianzhong, 2019. "Model predictive control based robust scheduling of community integrated energy system with operational flexibility," Applied Energy, Elsevier, vol. 243(C), pages 250-265.
    19. Wang, Kaifeng & Ye, Lin & Yang, Shihui & Deng, Zhanfeng & Song, Jieying & Li, Zhuo & Zhao, Yongning, 2023. "A hierarchical dispatch strategy of hybrid energy storage system in internet data center with model predictive control," Applied Energy, Elsevier, vol. 331(C).
    20. Hemmati, Reza & Mehrjerdi, Hasan & Bornapour, Mosayeb, 2020. "Hybrid hydrogen-battery storage to smooth solar energy volatility and energy arbitrage considering uncertain electrical-thermal loads," Renewable Energy, Elsevier, vol. 154(C), pages 1180-1187.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Juan Moreno-Castro & Victor Samuel Ocaña Guevara & Lesyani Teresa León Viltre & Yandi Gallego Landera & Oscar Cuaresma Zevallos & Miguel Aybar-Mejía, 2023. "Microgrid Management Strategies for Economic Dispatch of Electricity Using Model Predictive Control Techniques: A Review," Energies, MDPI, vol. 16(16), pages 1-24, August.
    2. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2023. "Distributed economic predictive control of integrated energy systems for enhanced synergy and grid response: A decomposition and cooperation strategy," Applied Energy, Elsevier, vol. 349(C).
    3. Changxing Yang & Xiaozhu Li & Laijun Chen & Shengwei Mei, 2024. "Intra-Day and Seasonal Peak Shaving Oriented Operation Strategies for Electric–Hydrogen Hybrid Energy Storage in Isolated Energy Systems," Sustainability, MDPI, vol. 16(16), pages 1-18, August.
    4. Quan, Shengwei & Wang, Ya-Xiong & Xiao, Xuelian & He, Hongwen & Sun, Fengchun, 2021. "Feedback linearization-based MIMO model predictive control with defined pseudo-reference for hydrogen regulation of automotive fuel cells," Applied Energy, Elsevier, vol. 293(C).
    5. Kneiske, T.M. & Braun, M. & Hidalgo-Rodriguez, D.I., 2018. "A new combined control algorithm for PV-CHP hybrid systems," Applied Energy, Elsevier, vol. 210(C), pages 964-973.
    6. Wei, Shangshang & Gao, Xianhua & Zhang, Yi & Li, Yiguo & Shen, Jiong & Li, Zuyi, 2021. "An improved stochastic model predictive control operation strategy of integrated energy system based on a single-layer multi-timescale framework," Energy, Elsevier, vol. 235(C).
    7. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2022. "Economic model predictive control of integrated energy systems: A multi-time-scale framework," Applied Energy, Elsevier, vol. 328(C).
    8. Fan, Guozhu & Peng, Chunhua & Wang, Xuekui & Wu, Peng & Yang, Yifan & Sun, Huijuan, 2024. "Optimal scheduling of integrated energy system considering renewable energy uncertainties based on distributionally robust adaptive MPC," Renewable Energy, Elsevier, vol. 226(C).
    9. Hu, Jiefeng & Xu, Yinliang & Cheng, Ka Wai & Guerrero, Josep M., 2018. "A model predictive control strategy of PV-Battery microgrid under variable power generations and load conditions," Applied Energy, Elsevier, vol. 221(C), pages 195-203.
    10. Yao, Leyi & Liu, Zeyuan & Chang, Weiguang & Yang, Qiang, 2023. "Multi-level model predictive control based multi-objective optimal energy management of integrated energy systems considering uncertainty," Renewable Energy, Elsevier, vol. 212(C), pages 523-537.
    11. Li, Yuxuan & Zhang, Junli & Wu, Xiao & Shen, Jiong & Maréchal, François, 2023. "Stochastic-robust planning optimization method based on tracking-economy extreme scenario tradeoff for CCHP multi-energy system," Energy, Elsevier, vol. 283(C).
    12. Alexander Holtwerth & André Xhonneux & Dirk Müller, 2024. "Model Predictive Control of a Stand-Alone Hybrid Battery-Hydrogen Energy System: A Case Study of the PHOEBUS Energy System," Energies, MDPI, vol. 17(18), pages 1-46, September.
    13. He, Yi & Guo, Su & Dong, Peixin & Wang, Chen & Huang, Jing & Zhou, Jianxu, 2022. "Techno-economic comparison of different hybrid energy storage systems for off-grid renewable energy applications based on a novel probabilistic reliability index," Applied Energy, Elsevier, vol. 328(C).
    14. Fan, Guangyao & Liu, Zhijian & Liu, Xuan & Shi, Yaxin & Wu, Di & Guo, Jiacheng & Zhang, Shicong & Yang, Xinyan & Zhang, Yulong, 2022. "Two-layer collaborative optimization for a renewable energy system combining electricity storage, hydrogen storage, and heat storage," Energy, Elsevier, vol. 259(C).
    15. Gimara Rajapakse & Shantha Jayasinghe & Alan Fleming & Michael Negnevitsky, 2017. "A Model Predictive Control-Based Power Converter System for Oscillating Water Column Wave Energy Converters," Energies, MDPI, vol. 10(10), pages 1-17, October.
    16. Fang, Debin & Wang, Pengyu, 2023. "Optimal real-time pricing and electricity package by retail electric providers based on social learning," Energy Economics, Elsevier, vol. 117(C).
    17. Restrepo, Mauricio & Cañizares, Claudio A. & Simpson-Porco, John W. & Su, Peter & Taruc, John, 2021. "Optimization- and Rule-based Energy Management Systems at the Canadian Renewable Energy Laboratory microgrid facility," Applied Energy, Elsevier, vol. 290(C).
    18. Hegde, Bharatkumar & Ahmed, Qadeer & Rizzoni, Giorgio, 2020. "Velocity and energy trajectory prediction of electrified powertrain for look ahead control," Applied Energy, Elsevier, vol. 279(C).
    19. Ma, Yixiang & Yu, Lean & Zhang, Guoxing & Lu, Zhiming & Wu, Jiaqian, 2023. "Source-load uncertainty-based multi-objective multi-energy complementary optimal scheduling," Renewable Energy, Elsevier, vol. 219(P1).
    20. Zhu, Jianhua & Peng, Yan & Gong, Zhuping & Sun, Yanming & Lai, Chaoan & Wang, Qing & Zhu, Xiaojun & Gan, Zhongxue, 2019. "Dynamic analysis of SNG and PNG supply: The stability and robustness view #," Energy, Elsevier, vol. 185(C), pages 717-729.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223024003. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.