IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i6p2033-d768351.html
   My bibliography  Save this article

A Collaborative Optimization Model for Integrated Energy System Considering Multi-Load Demand Response

Author

Listed:
  • Gejirifu De

    (State Grid Economic and Technological Research Ifigurenstitute Co., Ltd., Beijing 102209, China
    Department of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Xinlei Wang

    (State Grid Economic and Technological Research Ifigurenstitute Co., Ltd., Beijing 102209, China)

  • Xueqin Tian

    (State Grid Economic and Technological Research Ifigurenstitute Co., Ltd., Beijing 102209, China)

  • Tong Xu

    (State Grid Economic and Technological Research Ifigurenstitute Co., Ltd., Beijing 102209, China)

  • Zhongfu Tan

    (Department of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

The integrated demand response strategy participates in the coordinated operation of the integrated energy system, which can effectively improve the flexibility and stability of the system operation. This paper adopts a multiple load demand response strategy to guide users’ energy consumption habits. Firstly, the cooperative operation structure of integrated energy system considering comprehensive demand response is designed by analyzing the characteristics of multiple loads. Secondly, according to the interactive relationship between the output exchange power and the demand response adjustment of units, a two-stage collaborative optimization model is established. Finally, results show that considering the demand response of electricity-heat-gas load requires higher output power flexibility of the generators and enhances the ability of the system to participate in the demand response. The overall economic benefit of the system can be improved, but the comprehensive satisfaction of users will be reduced.

Suggested Citation

  • Gejirifu De & Xinlei Wang & Xueqin Tian & Tong Xu & Zhongfu Tan, 2022. "A Collaborative Optimization Model for Integrated Energy System Considering Multi-Load Demand Response," Energies, MDPI, vol. 15(6), pages 1-26, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2033-:d:768351
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/6/2033/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/6/2033/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuan, Guanxiu & Gao, Yan & Ye, Bei, 2021. "Optimal dispatching strategy and real-time pricing for multi-regional integrated energy systems based on demand response," Renewable Energy, Elsevier, vol. 179(C), pages 1424-1446.
    2. Gejirifu De & Zhongfu Tan & Menglu Li & Liling Huang & Xueying Song, 2018. "Two-Stage Stochastic Optimization for the Strategic Bidding of a Generation Company Considering Wind Power Uncertainty," Energies, MDPI, vol. 11(12), pages 1-21, December.
    3. Zhang, Ning & Sun, Qiuye & Yang, Lingxiao, 2021. "A two-stage multi-objective optimal scheduling in the integrated energy system with We-Energy modeling," Energy, Elsevier, vol. 215(PB).
    4. Yang, Dechang & Wang, Ming & Yang, Ruiqi & Zheng, Yingying & Pandzic, Hrvoje, 2021. "Optimal dispatching of an energy system with integrated compressed air energy storage and demand response," Energy, Elsevier, vol. 234(C).
    5. Wang, Lixiao & Jing, Z.X. & Zheng, J.H. & Wu, Q.H. & Wei, Feng, 2018. "Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals," Energy, Elsevier, vol. 158(C), pages 607-622.
    6. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "Hybrid time-scale energy optimal scheduling strategy for integrated energy system with bilateral interaction with supply and demand," Applied Energy, Elsevier, vol. 285(C).
    7. Wei, F. & Wu, Q.H. & Jing, Z.X. & Chen, J.J. & Zhou, X.X., 2016. "Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach," Energy, Elsevier, vol. 111(C), pages 933-946.
    8. Chen, Zexing & Zhang, Yongjun & Tang, Wenhu & Lin, Xiaoming & Li, Qifeng, 2019. "Generic modelling and optimal day-ahead dispatch of micro-energy system considering the price-based integrated demand response," Energy, Elsevier, vol. 176(C), pages 171-183.
    9. Mu, Yunfei & Chen, Wanqing & Yu, Xiaodan & Jia, Hongjie & Hou, Kai & Wang, Congshan & Meng, Xianjun, 2020. "A double-layer planning method for integrated community energy systems with varying energy conversion efficiencies," Applied Energy, Elsevier, vol. 279(C).
    10. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Razzak, Abdur & Islam, Md. Tariqul & Roy, Palash & Razzaque, Md. Abdur & Hassan, Md. Rafiul & Hassan, Mohammad Mehedi, 2024. "Leveraging Deep Q-Learning to maximize consumer quality of experience in smart grid," Energy, Elsevier, vol. 290(C).

    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. Pu, Yuchen & Li, Qi & Zou, Xueli & Li, Ruirui & Li, Luoyi & Chen, Weirong & Liu, Hong, 2021. "Optimal sizing for an integrated energy system considering degradation and seasonal hydrogen storage," Applied Energy, Elsevier, vol. 302(C).
    2. Chen, Changming & Wu, Xueyan & Li, Yan & Zhu, Xiaojun & Li, Zesen & Ma, Jien & Qiu, Weiqiang & Liu, Chang & Lin, Zhenzhi & Yang, Li & Wang, Qin & Ding, Yi, 2021. "Distributionally robust day-ahead scheduling of park-level integrated energy system considering generalized energy storages," Applied Energy, Elsevier, vol. 302(C).
    3. Zeljković, Čedomir & Mršić, Predrag & Erceg, Bojan & Lekić, Đorđe & Kitić, Nemanja & Matić, Petar, 2022. "Optimal sizing of photovoltaic-wind-diesel-battery power supply for mobile telephony base stations," Energy, Elsevier, vol. 242(C).
    4. He, Shuaijia & Gao, Hongjun & Liu, Junyong & Zhang, Xi & Chen, Zhe, 2022. "Distribution system planning considering peak shaving of energy station," Applied Energy, Elsevier, vol. 312(C).
    5. Wang, Yudong & Hu, Junjie, 2023. "Two-stage energy management method of integrated energy system considering pre-transaction behavior of energy service provider and users," Energy, Elsevier, vol. 271(C).
    6. Chen, Jing & Li, Fan & Li, Haoran & Sun, Bo & Zhang, Chenghui & Liu, Shuai, 2023. "Novel dynamic equivalent circuit model of integrated energy systems," Energy, Elsevier, vol. 262(PA).
    7. Zhang, Chaoyi & Jiao, Zaibin & Liu, Junshan & Ning, Keer, 2023. "Robust planning and economic analysis of park-level integrated energy system considering photovoltaic/thermal equipment," Applied Energy, Elsevier, vol. 348(C).
    8. Jiang, Qian & Jia, Hongjie & Mu, Yunfei & Yu, Xiaodan & Wang, Zibo, 2024. "Bilateral planning and operation for integrated energy service provider and prosumers - A Nash bargaining-based method," Applied Energy, Elsevier, vol. 368(C).
    9. Wang, L.X. & Zheng, J.H. & Li, Z.G. & Jing, Z.X. & Wu, Q.H., 2022. "Order reduction method for high-order dynamic analysis of heterogeneous integrated energy systems," Applied Energy, Elsevier, vol. 308(C).
    10. Liu, Wenxia & Huang, Yuchen & Li, Zhengzhou & Yang, Yue & Yi, Fang, 2020. "Optimal allocation for coupling device in an integrated energy system considering complex uncertainties of demand response," Energy, Elsevier, vol. 198(C).
    11. Fan, Wei & Tan, Zhongfu & Li, Fanqi & Zhang, Amin & Ju, Liwei & Wang, Yuwei & De, Gejirifu, 2023. "A two-stage optimal scheduling model of integrated energy system based on CVaR theory implementing integrated demand response," Energy, Elsevier, vol. 263(PC).
    12. Wang, Tonghe & Hua, Haochen & Shi, Tianying & Wang, Rui & Sun, Yizhong & Naidoo, Pathmanathan, 2024. "A bi-level dispatch optimization of multi-microgrid considering green electricity consumption willingness under renewable portfolio standard policy," Applied Energy, Elsevier, vol. 356(C).
    13. Mehar Ullah & Daniel Gutierrez-Rojas & Eero Inkeri & Tero Tynjälä & Pedro H. J. Nardelli, 2022. "Operation of Power-to-X-Related Processes Based on Advanced Data-Driven Methods: A Comprehensive Review," Energies, MDPI, vol. 15(21), pages 1-17, October.
    14. Yang, Ting & Zhao, Liyuan & Li, Wei & Zomaya, Albert Y., 2021. "Dynamic energy dispatch strategy for integrated energy system based on improved deep reinforcement learning," Energy, Elsevier, vol. 235(C).
    15. Mingshan Mo & Xinrui Xiong & Yunlong Wu & Zuyao Yu, 2023. "Deep-Reinforcement-Learning-Based Low-Carbon Economic Dispatch for Community-Integrated Energy System under Multiple Uncertainties," Energies, MDPI, vol. 16(22), pages 1-18, November.
    16. Wang, Yongli & Guo, Lu & Wang, Yanan & Zhang, Yunfei & Zhang, Siwen & Liu, Zeqiang & Xing, Juntai & Liu, Ximei, 2024. "Bi-level programming optimization method of rural integrated energy system based on coupling coordination degree of energy equipment," Energy, Elsevier, vol. 298(C).
    17. Zhang, Han & Han, Zhonghe & Wu, Di & Li, Peng & Li, Peng, 2023. "Energy optimization and performance analysis of a novel integrated energy system coupled with solar thermal unit and preheated organic cycle under extended following electric load strategy," Energy, Elsevier, vol. 272(C).
    18. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    19. Zhu, Yilin & Xu, Yujie & Chen, Haisheng & Guo, Huan & Zhang, Hualiang & Zhou, Xuezhi & Shen, Haotian, 2023. "Optimal dispatch of a novel integrated energy system combined with multi-output organic Rankine cycle and hybrid energy storage," Applied Energy, Elsevier, vol. 343(C).
    20. Xiaozhi Gao & Han Xiao & Shiwei Xu & Hsiung-Cheng Lin & Pengyu Chang, 2024. "What Is the Optimal Solution for Scheduling Multiple Energy Systems? Overview and Analysis of Integrated Energy Co-Dispatch Models," Energies, MDPI, vol. 17(18), pages 1-25, September.

    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:gam:jeners:v:15:y:2022:i:6:p:2033-:d:768351. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.