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

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  • 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
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    1. 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.
    2. 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).
    3. 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).
    4. 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.
    5. 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).
    6. 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).
    7. 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.
    8. 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).
    9. 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).
    10. 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).
    11. 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.
    12. 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).
    13. 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).
    14. 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).
    15. 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).
    16. 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).
    17. 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).
    18. 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.
    19. 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).
    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.
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