IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v273y2023ics0360544223005315.html
   My bibliography  Save this article

Distributed collaborative operation strategies in multi-agent integrated energy system considering integrated demand response based on game theory

Author

Listed:
  • Li, Ke
  • Ye, Ning
  • Li, Shuzhen
  • Wang, Haiyang
  • Zhang, Chenghui

Abstract

As the conflict between energy and the environment intensifies, integrated energy system (IES) is an effective way to reduce tensions with difficulties about multi-energy coupling and multi-agent. This study proposed a multi-agent game operation strategy consisting of energy retailers, suppliers, and users with integrated demand response (IDR). This problem is formulated as a distributed bi-level optimization model with one leader and multi-followers, which is a Stackelberg game among them vertically, and a non-cooperative game between energy suppliers horizontally. The equilibrium of proposed game model is proved the existence and uniqueness, and is solved by a distributed algorithm through genetic algorithm nested quadratic programming. Finally, the effectiveness of the proposed method is verified by the case study in three scenarios. The results shows that the supply-side revenue are effectively improved by 8.57%, the demand-side costs are reduced 1.42% by game model and IDR, and improve the operation and stability of energy supply and utilization.

Suggested Citation

  • Li, Ke & Ye, Ning & Li, Shuzhen & Wang, Haiyang & Zhang, Chenghui, 2023. "Distributed collaborative operation strategies in multi-agent integrated energy system considering integrated demand response based on game theory," Energy, Elsevier, vol. 273(C).
    • Handle: RePEc:eee:energy:v:273:y:2023:i:c:s0360544223005315
    DOI: 10.1016/j.energy.2023.127137
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223005315
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.127137?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. Jiang, Qian & Mu, Yunfei & Jia, Hongjie & Cao, Yan & Wang, Zibo & Wei, Wei & Hou, Kai & Yu, Xiaodan, 2022. "A Stackelberg Game-based planning approach for integrated community energy system considering multiple participants," Energy, Elsevier, vol. 258(C).
    2. Jordehi, A. Rezaee & Javadi, Mohammad Sadegh & Catalão, João P.S., 2021. "Day-ahead scheduling of energy hubs with parking lots for electric vehicles considering uncertainties," Energy, Elsevier, vol. 229(C).
    3. Lee, Won-Poong & Han, Dongjun & Won, Dongjun, 2022. "Grid-Oriented Coordination Strategy of Prosumers Using Game-theoretic Peer-to-Peer Trading Framework in Energy Community," Applied Energy, Elsevier, vol. 326(C).
    4. Ghanbari, Ali & Karimi, Hamid & Jadid, Shahram, 2020. "Optimal planning and operation of multi-carrier networked microgrids considering multi-energy hubs in distribution networks," Energy, Elsevier, vol. 204(C).
    5. Wei, F. & Jing, Z.X. & Wu, Peter Z. & Wu, Q.H., 2017. "A Stackelberg game approach for multiple energies trading in integrated energy systems," Applied Energy, Elsevier, vol. 200(C), pages 315-329.
    6. Yang, Shenbo & Tan, Zhongfu & Lin, Hongyu & Li, Peng & De, Gejirifu & Zhou, Feng’ao & Ju, Liwei, 2020. "A two-stage optimization model for Park Integrated Energy System operation and benefit allocation considering the effect of Time-Of-Use energy price," Energy, Elsevier, vol. 195(C).
    7. Zhuang, Wennan & Zhou, Suyang & Gu, Wei & Chen, Xiaogang, 2021. "Optimized dispatching of city-scale integrated energy system considering the flexibilities of city gas gate station and line packing," Applied Energy, Elsevier, vol. 290(C).
    8. 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).
    9. Si, Fangyuan & Han, Yinghua & Zhao, Qiang & Wang, Jinkuan, 2020. "Cost-effective operation of the urban energy system with variable supply and demand via coordination of multi-energy flows," Energy, Elsevier, vol. 203(C).
    10. Zheng, Shunlin & Sun, Yi & Li, Bin & Qi, Bing & Zhang, Xudong & Li, Fei, 2021. "Incentive-based integrated demand response for multiple energy carriers under complex uncertainties and double coupling effects," Applied Energy, Elsevier, vol. 283(C).
    11. Jiang, Yanni & Zhou, Kaile & Lu, Xinhui & Yang, Shanlin, 2020. "Electricity trading pricing among prosumers with game theory-based model in energy blockchain environment," Applied Energy, Elsevier, vol. 271(C).
    12. Naghikhani, Ali & Hosseini, Seyed Mohammad Hassan, 2022. "Optimal thermal and power planning considering economic and environmental issues in peak load management," Energy, Elsevier, vol. 239(PA).
    13. Koirala, Binod Prasad & Koliou, Elta & Friege, Jonas & Hakvoort, Rudi A. & Herder, Paulien M., 2016. "Energetic communities for community energy: A review of key issues and trends shaping integrated community energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 722-744.
    14. Wang, Yongli & Li, Fang & Yang, Jiale & Zhou, Minhan & Song, Fuhao & Zhang, Danyang & Xue, Lu & Zhu, Jinrong, 2020. "Demand response evaluation of RIES based on improved matter-element extension model," Energy, Elsevier, vol. 212(C).
    15. Xiang, Yue & Cai, Hanhu & Gu, Chenghong & Shen, Xiaodong, 2020. "Cost-benefit analysis of integrated energy system planning considering demand response," Energy, Elsevier, vol. 192(C).
    16. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N. & Burmester, Daniel, 2021. "Strategic design optimisation of multi-energy-storage-technology micro-grids considering a two-stage game-theoretic market for demand response aggregation," Applied Energy, Elsevier, vol. 287(C).
    17. Li, Songrui & Zhang, Lihui & Nie, Lei & Wang, Jianing, 2022. "Trading strategy and benefit optimization of load aggregators in integrated energy systems considering integrated demand response: A hierarchical Stackelberg game," Energy, Elsevier, vol. 249(C).
    18. Zhengjie Li & Zhisheng Zhang, 2021. "Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting," Energies, MDPI, vol. 14(9), pages 1-14, April.
    19. Lu, Qing & Lü, Shuaikang & Leng, Yajun, 2019. "A Nash-Stackelberg game approach in regional energy market considering users’ integrated demand response," Energy, Elsevier, vol. 175(C), pages 456-470.
    20. Eissa, M.M., 2019. "Developing incentive demand response with commercial energy management system (CEMS) based on diffusion model, smart meters and new communication protocol," Applied Energy, Elsevier, vol. 236(C), pages 273-292.
    21. Li, Jiamei & Ai, Qian & Yin, Shuangrui & Hao, Ran, 2022. "An aggregator-oriented hierarchical market mechanism for multi-type ancillary service provision based on the two-loop Stackelberg game," Applied Energy, Elsevier, vol. 323(C).
    22. Aviad Navon & Gefen Ben Yosef & Ram Machlev & Shmuel Shapira & Nilanjan Roy Chowdhury & Juri Belikov & Ariel Orda & Yoash Levron, 2020. "Applications of Game Theory to Design and Operation of Modern Power Systems: A Comprehensive Review," Energies, MDPI, vol. 13(15), pages 1-35, August.
    23. Vázquez-Canteli, José R. & Nagy, Zoltán, 2019. "Reinforcement learning for demand response: A review of algorithms and modeling techniques," Applied Energy, Elsevier, vol. 235(C), pages 1072-1089.
    24. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "Integrating supply and demand-side management in renewable-based energy systems," Energy, Elsevier, vol. 232(C).
    25. Li, Peng & Wang, Zixuan & Yang, Weihong & Liu, Haitao & Yin, Yunxing & Wang, Jiahao & Guo, Tianyu, 2021. "Hierarchically partitioned coordinated operation of distributed integrated energy system based on a master-slave game," Energy, Elsevier, vol. 214(C).
    26. Huang, Yujing & Wang, Yudong & Liu, Nian, 2022. "A two-stage energy management for heat-electricity integrated energy system considering dynamic pricing of Stackelberg game and operation strategy optimization," Energy, Elsevier, vol. 244(PA).
    27. Hua, Zhihao & Li, Jiayong & Zhou, Bin & Or, Siu Wing & Chan, Ka Wing & Meng, Yunfan, 2022. "Game-theoretic multi-energy trading framework for strategic biogas-solar renewable energy provider with heterogeneous consumers," Energy, Elsevier, vol. 260(C).
    28. Chauhan, Anurag & Saini, R.P., 2014. "A review on Integrated Renewable Energy System based power generation for stand-alone applications: Configurations, storage options, sizing methodologies and control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 99-120.
    29. Zhang, Guangming & Wang, Wei & Chen, Zhenyu & Li, Ruilian & Niu, Yuguang, 2022. "Modeling and optimal dispatch of a carbon-cycle integrated energy system for low-carbon and economic operation," Energy, Elsevier, vol. 240(C).
    30. Linglei Xu & Qiangqiang Xie & Liang Zheng & Yongzhu Hua & Lihuan Shao & Jiadong Cui, 2022. "Stackelberg-Game-Based Demand Response for Voltage Regulation in Distribution Network with High Penetration of Electric Vehicles," Energies, MDPI, vol. 15(10), pages 1-13, May.
    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. Long Wang, 2023. "Optimal Scheduling Strategy for Multi-Energy Microgrid Considering Integrated Demand Response," Energies, MDPI, vol. 16(12), pages 1-17, June.
    2. Zhou, Yuan & Wang, Jiangjiang & Yang, Mingxu & Xu, Hangwei, 2023. "Hybrid active and passive strategies for chance-constrained bilevel scheduling of community multi-energy system considering demand-side management and consumer psychology," Applied Energy, Elsevier, vol. 349(C).
    3. Zhihan Shi & Guangming Zhang & Xiaoxiong Zhou & Weisong Han & Mingxiang Zhu & Zhiqing Bai & Xiaodong Lv, 2023. "Research on Integrated Energy Distributed Sharing in Distribution Network Considering AC Power Flow and Demand Response," Sustainability, MDPI, vol. 15(22), pages 1-23, November.

    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. Luo, Xi & Liu, Yanfeng & Feng, Pingan & Gao, Yuan & Guo, Zhenxiang, 2021. "Optimization of a solar-based integrated energy system considering interaction between generation, network, and demand side," Applied Energy, Elsevier, vol. 294(C).
    2. Wu, Qiong & Xie, Zhun & Ren, Hongbo & Li, Qifen & Yang, Yongwen, 2022. "Optimal trading strategies for multi-energy microgrid cluster considering demand response under different trading modes: A comparison study," Energy, Elsevier, vol. 254(PC).
    3. Li, Songrui & Zhang, Lihui & Nie, Lei & Wang, Jianing, 2022. "Trading strategy and benefit optimization of load aggregators in integrated energy systems considering integrated demand response: A hierarchical Stackelberg game," Energy, Elsevier, vol. 249(C).
    4. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "A novel bi-level robust game model to optimize a regionally integrated energy system with large-scale centralized renewable-energy sources in Western China," Energy, Elsevier, vol. 228(C).
    5. Zhihan Shi & Weisong Han & Guangming Zhang & Zhiqing Bai & Mingxiang Zhu & Xiaodong Lv, 2022. "Research on Low-Carbon Energy Sharing through the Alliance of Integrated Energy Systems with Multiple Uncertainties," Energies, MDPI, vol. 15(24), pages 1-20, December.
    6. 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).
    7. Gayo-Abeleira, Miguel & Santos, Carlos & Javier Rodríguez Sánchez, Francisco & Martín, Pedro & Antonio Jiménez, José & Santiso, Enrique, 2022. "Aperiodic two-layer energy management system for community microgrids based on blockchain strategy," Applied Energy, Elsevier, vol. 324(C).
    8. Aslani, Mehrdad & Mashayekhi, Mehdi & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2022. "Robust optimal operation of energy hub incorporating integrated thermal and electrical demand response programs under various electric vehicle charging modes," Applied Energy, Elsevier, vol. 321(C).
    9. 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).
    10. Mu, Yunfei & Wang, Congshan & Cao, Yan & Jia, Hongjie & Zhang, Qingzhu & Yu, Xiaodan, 2022. "A CVaR-based risk assessment method for park-level integrated energy system considering the uncertainties and correlation of energy prices," Energy, Elsevier, vol. 247(C).
    11. Hernandez-Matheus, Alejandro & Löschenbrand, Markus & Berg, Kjersti & Fuchs, Ida & Aragüés-Peñalba, Mònica & Bullich-Massagué, Eduard & Sumper, Andreas, 2022. "A systematic review of machine learning techniques related to local energy communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    12. Meifang Wei & Youyue Deng & Min Long & Yahui Wang & Yong Li, 2022. "Transaction Model Based on Stackelberg Game Method for Balancing Supply and Demand Sides of Multi-Energy Microgrid," Energies, MDPI, vol. 15(4), pages 1-20, February.
    13. Yi Kuang & Xiuli Wang & Hongyang Zhao & Yijun Huang & Xianlong Chen & Xifan Wang, 2020. "Agent-Based Energy Sharing Mechanism Using Deep Deterministic Policy Gradient Algorithm," Energies, MDPI, vol. 13(19), pages 1-20, September.
    14. Zhou, Yuan & Wang, Jiangjiang & Yang, Mingxu & Xu, Hangwei, 2023. "Hybrid active and passive strategies for chance-constrained bilevel scheduling of community multi-energy system considering demand-side management and consumer psychology," Applied Energy, Elsevier, vol. 349(C).
    15. 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).
    16. Jiajia Li & Jinfu Liu & Peigang Yan & Xingshuo Li & Guowen Zhou & Daren Yu, 2021. "Operation Optimization of Integrated Energy System under a Renewable Energy Dominated Future Scene Considering Both Independence and Benefit: A Review," Energies, MDPI, vol. 14(4), pages 1-36, February.
    17. 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).
    18. Yang, Jie & Ma, Tieding & Ma, Kai & Yang, Bo & Guerrero, Josep M. & Liu, Zhixin, 2021. "Trading mechanism and pricing strategy of integrated energy systems based on credit rating and Bayesian game," Energy, Elsevier, vol. 232(C).
    19. Lv, Chaoxian & Liang, Rui & Zhang, Ge & Zhang, Xiaotong & Jin, Wei, 2023. "Energy accommodation-oriented interaction of active distribution network and central energy station considering soft open points," Energy, Elsevier, vol. 268(C).
    20. Wang, Hao-ran & Feng, Tian-tian & Xiong, Wei, 2022. "How can the dynamic game be integrated into blockchain-based distributed energy resources multi-agent transactions for decision-making?," Energy, Elsevier, vol. 254(PB).

    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:273:y:2023:i:c:s0360544223005315. 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.