IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v342y2023ics0306261923005603.html
   My bibliography  Save this article

A tri-layer decision-making framework for IES considering the interaction of integrated demand response and multi-energy market clearing

Author

Listed:
  • Yao, Wenliang
  • Wang, Chengfu
  • Yang, Ming
  • Wang, Kang
  • Dong, Xiaoming
  • Zhang, Zhenwei

Abstract

In integrated energy system (IES), rapidly developmental integrated demand response (IDR) increases the demand-side flexibility. It is challenging to aggregate decentralized IDR resources to participate in multiple markets simultaneously with coordinating the profits of all market-driven stakeholders. To this end, this paper proposes a novel tri-layer decision-making framework for IES to investigate the interaction of IDR and multi-energy market clearing while coordinate complexly interactive stakeholders. In the first layer, electricity-gas wholesale market is cleared based on the offers and bids submitted by energy producers and integrated energy distribution system operator (IEDSO). In the second layer, IEDSO serves as a mediator between multi-energy market and integrated load aggregators (ILAs). Profit-maximizing IEDSO affects the market equilibrium prices by incorporating IDR resources to trade strategically in wholesale market, and offers flexible price strategies considering the changes in clearing results to exploit ILAs’ IDR potential. In the third layer, cooperative game theory is introduced to make ILAs can flexibly cooperate with each other or participate in IDR according to price signals, and Shapley value is used to avoid the conflicts of interest. Meanwhile, multiple uncertainties are dealt with by scenario method to mitigate their influence on multi-energy market operation. To solve this problem efficiently, a tailored reformulation and convexification scheme is developed to convert it into an equivalent mixed integer linear programming problem. Finally, case studies verify the effectiveness and practicality of the proposed tri-layer framework.

Suggested Citation

  • Yao, Wenliang & Wang, Chengfu & Yang, Ming & Wang, Kang & Dong, Xiaoming & Zhang, Zhenwei, 2023. "A tri-layer decision-making framework for IES considering the interaction of integrated demand response and multi-energy market clearing," Applied Energy, Elsevier, vol. 342(C).
  • Handle: RePEc:eee:appene:v:342:y:2023:i:c:s0306261923005603
    DOI: 10.1016/j.apenergy.2023.121196
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923005603
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2023.121196?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. Gu, Haifei & Li, Yang & Yu, Jie & Wu, Chen & Song, Tianli & Xu, Jinzhou, 2020. "Bi-level optimal low-carbon economic dispatch for an industrial park with consideration of multi-energy price incentives," Applied Energy, Elsevier, vol. 262(C).
    2. Guo, Bowei & Weeks, Melvyn, 2022. "Dynamic tariffs, demand response, and regulation in retail electricity markets," Energy Economics, Elsevier, vol. 106(C).
    3. Wang, Rutian & Wen, Xiangyun & Wang, Xiuyun & Fu, Yanbo & Zhang, Yu, 2022. "Low carbon optimal operation of integrated energy system based on carbon capture technology, LCA carbon emissions and ladder-type carbon trading," Applied Energy, Elsevier, vol. 311(C).
    4. Aussel, Didier & Brotcorne, Luce & Lepaul, Sébastien & von Niederhäusern, Léonard, 2020. "A trilevel model for best response in energy demand-side management," European Journal of Operational Research, Elsevier, vol. 281(2), pages 299-315.
    5. Pan, Chongchao & Jin, Tai & Li, Na & Wang, Guanxiong & Hou, Xiaowang & Gu, Yueqing, 2023. "Multi-objective and two-stage optimization study of integrated energy systems considering P2G and integrated demand responses," Energy, Elsevier, vol. 270(C).
    6. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K., 2021. "Cooperative negawatt P2P energy trading for low-voltage distribution networks," Applied Energy, Elsevier, vol. 299(C).
    7. Zare Oskouei, Morteza & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Shafiee, Mahmood & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "A hybrid robust-stochastic approach to evaluate the profit of a multi-energy retailer in tri-layer energy markets," Energy, Elsevier, vol. 214(C).
    8. Coelho, António & Iria, José & Soares, Filipe, 2021. "Network-secure bidding optimization of aggregators of multi-energy systems in electricity, gas, and carbon markets," Applied Energy, Elsevier, vol. 301(C).
    9. Wang, Ni & Liu, Ziyi & Heijnen, Petra & Warnier, Martijn, 2022. "A peer-to-peer market mechanism incorporating multi-energy coupling and cooperative behaviors," Applied Energy, Elsevier, vol. 311(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).
    11. 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).
    12. Li, Junkai & Ge, Shaoyun & Xu, Zhengyang & Liu, Hong & Li, Jifeng & Wang, Chengshan & Cheng, Xueying, 2023. "A network-secure peer-to-peer trading framework for electricity-carbon integrated market among local prosumers," Applied Energy, Elsevier, vol. 335(C).
    13. Wang, Lu & Gu, Wei & Wu, Zhi & Qiu, Haifeng & Pan, Guangsheng, 2020. "Non-cooperative game-based multilateral contract transactions in power-heating integrated systems," Applied Energy, Elsevier, vol. 268(C).
    14. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    15. Pan, Guangsheng & Gu, Wei & Wu, Zhi & Lu, Yuping & Lu, Shuai, 2019. "Optimal design and operation of multi-energy system with load aggregator considering nodal energy prices," Applied Energy, Elsevier, vol. 239(C), pages 280-295.
    16. Wang, Yubin & Dong, Wei & Yang, Qiang, 2022. "Multi-stage optimal energy management of multi-energy microgrid in deregulated electricity markets," Applied Energy, Elsevier, vol. 310(C).
    17. Duan, Jiandong & Liu, Fan & Yang, Yao, 2022. "Optimal operation for integrated electricity and natural gas systems considering demand response uncertainties," Applied Energy, Elsevier, vol. 323(C).
    18. Wang, Haiyang & Zhang, Chenghui & Li, Ke & Liu, Shuai & Li, Shuzhen & Wang, Yu, 2021. "Distributed coordinative transaction of a community integrated energy system based on a tri-level game model," Applied Energy, Elsevier, vol. 295(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. Zhao, Naixin & Gu, Wenbo & Zheng, Zipeng & Ma, Tao, 2023. "Multi-objective bi-level planning of the integrated energy system considering uncertain user loads and carbon emission during the equipment manufacturing process," Renewable Energy, Elsevier, vol. 216(C).
    2. Long Wang, 2023. "Optimal Scheduling Strategy for Multi-Energy Microgrid Considering Integrated Demand Response," Energies, MDPI, vol. 16(12), pages 1-17, June.
    3. Ju, Liwei & Lv, ShuoShuo & Zhang, Zheyu & Li, Gen & Gan, Wei & Fang, Jiangpeng, 2024. "Data-driven two-stage robust optimization dispatching model and benefit allocation strategy for a novel virtual power plant considering carbon-green certificate equivalence conversion mechanism," Applied Energy, Elsevier, vol. 362(C).
    4. Zhao, Wei & Liao, Qi & Qiu, Rui & Liu, Chunying & Xu, Ning & Yu, Xiao & Liang, Yongtu, 2024. "Pipe sharing: A bilevel optimization model for the optimal capacity allocation of natural gas network," Applied Energy, Elsevier, vol. 359(C).
    5. 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.
    6. Mishra, Mrityunjay Kumar & Al-Sumaiti, Ameena Saad & Murari, Krishna & Parida, S.K. & Jaafari, Khaled Al, 2024. "Strategic interaction among distribution network operator and residential end-users via distribution use of system charges in demand-side management environment," Applied Energy, Elsevier, vol. 364(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. Wang, Haibing & Zhao, Anjie & Khan, Muhammad Qasim & Sun, Weiqing, 2024. "Optimal operation of energy hub considering reward-punishment ladder carbon trading and electrothermal demand coupling," Energy, Elsevier, vol. 286(C).
    2. Xu, Xun & Shao, Zhenguo & Chen, Feixiong & Cheng, Guoyang, 2024. "Multi-game optimization operation strategy for integrated energy system considering spatiotemporal correlation of renewable energy," Energy, Elsevier, vol. 303(C).
    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. Zheng, Shunlin & Qi, Qi & Sun, Yi & Ai, Xin, 2023. "Integrated demand response considering substitute effect and time-varying response characteristics under incomplete information," Applied Energy, Elsevier, vol. 333(C).
    5. 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).
    6. Ma, Siyuan & Mi, Yang & Shi, Shuai & Li, Dongdong & Xing, Haijun & Wang, Peng, 2024. "Low-carbon economic operation of energy hub integrated with linearization model and nodal energy-carbon price," Energy, Elsevier, vol. 294(C).
    7. Christina Papadimitriou & Marialaura Di Somma & Chrysanthos Charalambous & Martina Caliano & Valeria Palladino & Andrés Felipe Cortés Borray & Amaia González-Garrido & Nerea Ruiz & Giorgio Graditi, 2023. "A Comprehensive Review of the Design and Operation Optimization of Energy Hubs and Their Interaction with the Markets and External Networks," Energies, MDPI, vol. 16(10), pages 1-46, May.
    8. Wu, Chun & Chen, Xingying & Hua, Haochen & Yu, Kun & Gan, Lei & Shen, Jun & Ding, Yi, 2024. "Peer-to-peer energy trading optimization for community prosumers considering carbon cap-and-trade," Applied Energy, Elsevier, vol. 358(C).
    9. 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).
    10. Zeng, Huibin & Shao, Bilin & Dai, Hongbin & Yan, Yichuan & Tian, Ning, 2023. "Natural gas demand response strategy considering user satisfaction and load volatility under dynamic pricing," Energy, Elsevier, vol. 277(C).
    11. Gu, Haifei & Li, Yang & Yu, Jie & Wu, Chen & Song, Tianli & Xu, Jinzhou, 2020. "Bi-level optimal low-carbon economic dispatch for an industrial park with consideration of multi-energy price incentives," Applied Energy, Elsevier, vol. 262(C).
    12. Cai, Qiran & Xu, Qingyang & Qing, Jing & Shi, Gang & Liang, Qiao-Mei, 2022. "Promoting wind and photovoltaics renewable energy integration through demand response: Dynamic pricing mechanism design and economic analysis for smart residential communities," Energy, Elsevier, vol. 261(PB).
    13. Liu, Fan & Duan, Jiandong & Wu, Chen & Tian, Qinxing, 2024. "Risk-averse distributed optimization for integrated electricity-gas systems considering uncertainties of Wind-PV and power-to-gas," Renewable Energy, Elsevier, vol. 227(C).
    14. Ding, Jianyong & Gao, Ciwei & Song, Meng & Yan, Xingyu & Chen, Tao, 2022. "Bi-level optimal scheduling of virtual energy station based on equal exergy replacement mechanism," Applied Energy, Elsevier, vol. 327(C).
    15. Zhang, Xinyue & Guo, Xiaopeng & Zhang, Xingping, 2023. "Bidding modes for renewable energy considering electricity-carbon integrated market mechanism based on multi-agent hybrid game," Energy, Elsevier, vol. 263(PA).
    16. Innocent Kamwa & Leila Bagherzadeh & Atieh Delavari, 2023. "Integrated Demand Response Programs in Energy Hubs: A Review of Applications, Classifications, Models and Future Directions," Energies, MDPI, vol. 16(11), pages 1-21, May.
    17. Liang, Ziwen & Mu, Longhua, 2024. "Multi-agent low-carbon optimal dispatch of regional integrated energy system based on mixed game theory," Energy, Elsevier, vol. 295(C).
    18. Yun, Yunyun & Zhang, Dahai & Yang, Shengchun & Li, Yaping & Yan, Jiahao, 2023. "Low-carbon optimal dispatch of integrated energy system considering the operation of oxy-fuel combustion coupled with power-to-gas and hydrogen-doped gas equipment," Energy, Elsevier, vol. 283(C).
    19. Wang, Yubin & Yang, Qiang & Zhou, Yue & Zheng, Yanchong, 2024. "A risk-averse day-ahead bidding strategy of transactive energy sharing microgrids with data-driven chance constraints," Applied Energy, Elsevier, vol. 353(PB).
    20. Wang, Yongli & Liu, Zhen & Wang, Jingyan & Du, Boxin & Qin, Yumeng & Liu, Xiaoli & Liu, Lin, 2023. "A Stackelberg game-based approach to transaction optimization for distributed integrated energy system," Energy, Elsevier, vol. 283(C).

    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:appene:v:342:y:2023:i:c:s0306261923005603. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.