IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v251y2022ics0360544222008179.html
   My bibliography  Save this article

Day-ahead energy pricing and management method for regional integrated energy systems considering multi-energy demand responses

Author

Listed:
  • Zhu, Xu
  • Sun, Yuanzhang
  • Yang, Jun
  • Dou, Zhenlan
  • Li, Gaojunjie
  • Xu, Chengying
  • Wen, Yuxin

Abstract

By coupling multiple energy networks, an integrated energy system can realize the conversion and complementarity of various energy sources. The development of regional integrated energy systems (RIESs) has brought both opportunities and challenges to the energy market. Without a reasonable integrated energy day-ahead trading structure, it is difficult for energy providers to make profits and for consumers to achieve economic energy utilization. At the same time, various user-side energy loads are controllable, and it is necessary to comprehensively consider multi-energy demand responses in energy trading and management. To address the above issues, the trading behaviors of main market players are clarified, and an integrated energy pricing and management strategy is proposed in this paper. Multi-energy demand response models for data centers, electric vehicles (EVs) and air conditioning loads (ACLs) are also established. Considering multi-energy demand responses, a day-ahead energy pricing and management model for RIESs is proposed. The model is a bilevel Stackelberg game optimization model, in which the upper level considers profit maximization of energy service provider (ESP) while the lower level deals with the cost minimization of energy consumer (EC). Based on simulation analysis, the feasibility of the proposed model is verified. The trading scheme optimized by this model can benefit both ESP and EC. Compared with a traditional integrated energy trading structure, the profit source of ESP is enlarged. The simulation results also show that the application of multi-energy demand responses can improve the economic and collaborative operation effect of RIESs and reduce carbon emissions.

Suggested Citation

  • Zhu, Xu & Sun, Yuanzhang & Yang, Jun & Dou, Zhenlan & Li, Gaojunjie & Xu, Chengying & Wen, Yuxin, 2022. "Day-ahead energy pricing and management method for regional integrated energy systems considering multi-energy demand responses," Energy, Elsevier, vol. 251(C).
    • Handle: RePEc:eee:energy:v:251:y:2022:i:c:s0360544222008179
    DOI: 10.1016/j.energy.2022.123914
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222008179
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.123914?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. Sobhani, Seyed Omid & Sheykhha, Siamak & Madlener, Reinhard, 2020. "An integrated two-level demand-side management game applied to smart energy hubs with storage," Energy, Elsevier, vol. 206(C).
    2. Liu, Peiyun & Ding, Tao & Zou, Zhixiang & Yang, Yongheng, 2019. "Integrated demand response for a load serving entity in multi-energy market considering network constraints," Applied Energy, Elsevier, vol. 250(C), pages 512-529.
    3. 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.
    4. Wang, Yifei & Wang, Xiuli & Shao, Chengcheng & Gong, Naiwei, 2020. "Distributed energy trading for an integrated energy system and electric vehicle charging stations: A Nash bargaining game approach," Renewable Energy, Elsevier, vol. 155(C), pages 513-530.
    5. Gu, Wei & Wang, Jun & Lu, Shuai & Luo, Zhao & Wu, Chenyu, 2017. "Optimal operation for integrated energy system considering thermal inertia of district heating network and buildings," Applied Energy, Elsevier, vol. 199(C), pages 234-246.
    6. Fan, Songli & Ai, Qian & Piao, Longjian, 2018. "Bargaining-based cooperative energy trading for distribution company and demand response," Applied Energy, Elsevier, vol. 226(C), pages 469-482.
    7. Zhou, Suyang & Sun, Kaiyu & Wu, Zhi & Gu, Wei & Wu, Gaoxiang & Li, Zhe & Li, Junjie, 2020. "Optimized operation method of small and medium-sized integrated energy system for P2G equipment under strong uncertainty," Energy, Elsevier, vol. 199(C).
    8. Orehounig, Kristina & Evins, Ralph & Dorer, Viktor, 2015. "Integration of decentralized energy systems in neighbourhoods using the energy hub approach," Applied Energy, Elsevier, vol. 154(C), pages 277-289.
    9. Hulshof, Daan & van der Maat, Jan-Pieter & Mulder, Machiel, 2016. "Market fundamentals, competition and natural-gas prices," Energy Policy, Elsevier, vol. 94(C), pages 480-491.
    10. Visser, L.R. & Kootte, M.E. & Ferreira, A.C. & Sicurani, O. & Pauwels, E.J. & Vuik, C. & Van Sark, W.G.J.H.M. & AlSkaif, T.A., 2022. "An operational bidding framework for aggregated electric vehicles on the electricity spot market," Applied Energy, Elsevier, vol. 308(C).
    11. 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.
    12. Wang, Yongli & Ma, Yuze & Song, Fuhao & Ma, Yang & Qi, Chengyuan & Huang, Feifei & Xing, Juntai & Zhang, Fuwei, 2020. "Economic and efficient multi-objective operation optimization of integrated energy system considering electro-thermal demand response," Energy, Elsevier, vol. 205(C).
    13. Ma, Tengfei & Pei, Wei & Xiao, Hao & Kong, Li & Mu, Yunfei & Pu, Tianjiao, 2020. "The energy management strategies based on dynamic energy pricing for community integrated energy system considering the interactions between suppliers and users," Energy, Elsevier, vol. 211(C).
    14. Aghamohammadloo, Hossein & Talaeizadeh, Valiollah & Shahanaghi, Kamran & Aghaei, Jamshid & Shayanfar, Heidarali & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Integrated Demand Response programs and energy hubs retail energy market modelling," Energy, Elsevier, vol. 234(C).
    15. Khaloie, Hooman & Abdollahi, Amir & Shafie-khah, Miadreza & Anvari-Moghaddam, Amjad & Nojavan, Sayyad & Siano, Pierluigi & Catalão, João P.S., 2020. "Coordinated wind-thermal-energy storage offering strategy in energy and spinning reserve markets using a multi-stage model," Applied Energy, Elsevier, vol. 259(C).
    16. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    17. Bloemhof, Barb, 2017. "Assessing consumer benefits in the Ontario residential retail natural gas market: ontario residential retail natural gas market: Why marketer entry did not help," Energy Policy, Elsevier, vol. 109(C), pages 555-564.
    18. Xu, Jianzhong & Sui, Jun & Li, Bingyu & Yang, Minlin, 2010. "Research, development and the prospect of combined cooling, heating, and power systems," Energy, Elsevier, vol. 35(11), pages 4361-4367.
    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. 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).
    2. 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).
    3. Zhao Luo & Jinghui Wang & Ni Xiao & Linyan Yang & Weijie Zhao & Jialu Geng & Tao Lu & Mengshun Luo & Chenming Dong, 2022. "Low Carbon Economic Dispatch Optimization of Regional Integrated Energy Systems Considering Heating Network and P2G," Energies, MDPI, vol. 15(15), pages 1-14, July.
    4. Qiuyi Hong & Fanlin Meng & Jian Liu, 2023. "Customised Multi-Energy Pricing: Model and Solutions," Energies, MDPI, vol. 16(4), pages 1-31, February.
    5. Wang, Liying & Lin, Jialin & Dong, Houqi & Wang, Yuqing & Zeng, Ming, 2023. "Demand response comprehensive incentive mechanism-based multi-time scale optimization scheduling for park integrated energy system," Energy, Elsevier, vol. 270(C).
    6. Mohammed Qais & K. H. Loo & Hany M. Hasanien & Saad Alghuwainem, 2023. "Optimal Comfortable Load Schedule for Home Energy Management Including Photovoltaic and Battery Systems," Sustainability, MDPI, vol. 15(12), pages 1-15, June.
    7. 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).
    8. Zhou, Kaile & Peng, Ning & Yin, Hui & Hu, Rong, 2023. "Urban virtual power plant operation optimization with incentive-based demand response," Energy, Elsevier, vol. 282(C).
    9. Mansouri, Seyed Amir & Rezaee Jordehi, Ahmad & Marzband, Mousa & Tostado-Véliz, Marcos & Jurado, Francisco & Aguado, José A., 2023. "An IoT-enabled hierarchical decentralized framework for multi-energy microgrids market management in the presence of smart prosumers using a deep learning-based forecaster," Applied Energy, Elsevier, vol. 333(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. 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.
    2. Dezhou Kong & Jianru Jing & Tingyue Gu & Xuanyue Wei & Xingning Sa & Yimin Yang & Zhiang Zhang, 2023. "Theoretical Analysis of Integrated Community Energy Systems (ICES) Considering Integrated Demand Response (IDR): A Review of the System Modelling and Optimization," Energies, MDPI, vol. 16(10), pages 1-22, May.
    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, 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).
    5. Zheng, Ling & Zhou, Bin & Cao, Yijia & Wing Or, Siu & Li, Yong & Wing Chan, Ka, 2022. "Hierarchical distributed multi-energy demand response for coordinated operation of building clusters," Applied Energy, Elsevier, vol. 308(C).
    6. 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).
    7. 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).
    8. Liu, Peiyun & Ding, Tao & Zou, Zhixiang & Yang, Yongheng, 2019. "Integrated demand response for a load serving entity in multi-energy market considering network constraints," Applied Energy, Elsevier, vol. 250(C), pages 512-529.
    9. 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).
    10. Li, Yuanzheng & Huang, Jingjing & Liu, Yun & Zhao, Tianyang & Zhou, Yue & Zhao, Yong & Yuen, Chau, 2022. "Day-ahead risk averse market clearing considering demand response with data-driven load uncertainty representation: A Singapore electricity market study," Energy, Elsevier, vol. 254(PA).
    11. Tang, Difei & Yang, Xiangguo & Yong, Jing & Xu, Wilsun, 2019. "Active method for mitigation of induced voltage in integrated energy systems," Applied Energy, Elsevier, vol. 235(C), pages 553-563.
    12. Li, Yuchun & Wang, Jinkuan & Zhang, Yan & Han, Yinghua, 2022. "Day-ahead scheduling strategy for integrated heating and power system with high wind power penetration and integrated demand response: A hybrid stochastic/interval approach," Energy, Elsevier, vol. 253(C).
    13. Chen, Sheng & Sun, Guoqiang & Wei, Zhinong & Wang, Dan, 2020. "Dynamic pricing in electricity and natural gas distribution networks: An EPEC model," Energy, Elsevier, vol. 207(C).
    14. 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).
    15. Georgios I. Tsoumalis & Zafeirios N. Bampos & Georgios V. Chatzis & Pandelis N. Biskas, 2022. "Overview of Natural Gas Boiler Optimization Technologies and Potential Applications on Gas Load Balancing Services," Energies, MDPI, vol. 15(22), pages 1-24, November.
    16. Tsoumalis, Georgios I. & Bampos, Zafeirios N. & Biskas, Pandelis N. & Keranidis, Stratos D. & Symeonidis, Polychronis A. & Voulgarakis, Dimitrios K., 2022. "A novel system for providing explicit demand response from domestic natural gas boilers," Applied Energy, Elsevier, vol. 317(C).
    17. Yi, Liqi & Li, Tao & Zhang, Ting, 2021. "Optimal investment selection of regional integrated energy system under multiple strategic objectives portfolio," Energy, Elsevier, vol. 218(C).
    18. 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).
    19. Li, Bo & Li, Xu & Su, Qingyu, 2022. "A system and game strategy for the isolated island electric-gas deeply coupled energy network," Applied Energy, Elsevier, vol. 306(PA).
    20. Chen, Yang & Park, Byungkwon & Kou, Xiao & Hu, Mengqi & Dong, Jin & Li, Fangxing & Amasyali, Kadir & Olama, Mohammed, 2020. "A comparison study on trading behavior and profit distribution in local energy transaction games," Applied Energy, Elsevier, vol. 280(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:energy:v:251:y:2022:i:c:s0360544222008179. 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.