IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v359y2024ics0306261924001065.html
   My bibliography  Save this article

Bi-level optimal operations for grid operator and low-carbon building prosumers with peer-to-peer energy sharing

Author

Listed:
  • Wang, Xiaoyu
  • Jia, Hongjie
  • Jin, Xiaolong
  • Mu, Yunfei
  • Wei, Wei
  • Yu, Xiaodan
  • Liang, Shuo

Abstract

Low-carbon buildings (LCBs) are normally equipped with distributed energy resources (DERs) such as photovoltaic (PV) panels and batteries, thereby creating LCB prosumers that both produce and consume energy. Peer-to-peer (P2P) energy sharing among LCB prosumers could bring higher economic benefits for themselves, and facilitate better local power balance for the power grid. To fully harness the benefits of P2P energy sharing for both LCB prosumers and the power grid, a bi-level optimization method for LCB prosumers and the power grid operator is proposed in this paper. The grid operator at the upper level imposes the optimal time-varying network charge to LCB prosumers at the lower level to maximize its profit. And LCB prosumers with the objective of minimizing their costs adjust the schedules including P2P energy sharing and their heating loads to respond to the grid operator's optimal network charge prices. Additionally, to further exploit the energy resources including heating loads in LCBs, the model predictive control (MPC) approach is integrated with the bi-level optimization in the presence of uncertainties. The bi-level optimization belongs to the NP-hard category, making it challenging to solve. To reduce the computational complexity, the bi-level optimization problem is converted to the single-level programming using Karush-Kuhn-Tucker (KKT) conditions. Numerical results illustrate that the bi-level optimization method can obtain a balanced scheduling scheme between the grid operator and LCB prosumers. In addition, incorporating the thermal inertia of building heating loads can provide more operational flexibility for both the grid operator and LCB prosumers. Furthermore, the costs of LCB prosumers based on MPC approach can be reduced with the decrease of forecast error level.

Suggested Citation

  • Wang, Xiaoyu & Jia, Hongjie & Jin, Xiaolong & Mu, Yunfei & Wei, Wei & Yu, Xiaodan & Liang, Shuo, 2024. "Bi-level optimal operations for grid operator and low-carbon building prosumers with peer-to-peer energy sharing," Applied Energy, Elsevier, vol. 359(C).
  • Handle: RePEc:eee:appene:v:359:y:2024:i:c:s0306261924001065
    DOI: 10.1016/j.apenergy.2024.122723
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924001065
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2024.122723?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. Wang, Zhaoxia & Zhao, Jing & Li, Meng, 2017. "Analysis and optimization of carbon trading mechanism for renewable energy application in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 435-451.
    2. Yang, Yingchun & Liu, Jianghua & Lin, Yingying & Li, Qiongyuan, 2019. "The impact of urbanization on China’s residential energy consumption," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 170-182.
    3. Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie, 2020. "A distributed Peer-to-Peer energy transaction method for diversified prosumers in Urban Community Microgrid System," Applied Energy, Elsevier, vol. 260(C).
    4. 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).
    5. Lyu, Cheng & Jia, Youwei & Xu, Zhao, 2021. "Fully decentralized peer-to-peer energy sharing framework for smart buildings with local battery system and aggregated electric vehicles," Applied Energy, Elsevier, vol. 299(C).
    6. Jiang, Tao & Li, Zening & Jin, Xiaolong & Chen, Houhe & Li, Xue & Mu, Yunfei, 2018. "Flexible operation of active distribution network using integrated smart buildings with heating, ventilation and air-conditioning systems," Applied Energy, Elsevier, vol. 226(C), pages 181-196.
    7. Zhou, Yue & Wang, Chengshan & Wu, Jianzhong & Wang, Jidong & Cheng, Meng & Li, Gen, 2017. "Optimal scheduling of aggregated thermostatically controlled loads with renewable generation in the intraday electricity market," Applied Energy, Elsevier, vol. 188(C), pages 456-465.
    8. Thomas Morstyn & Niall Farrell & Sarah J. Darby & Malcolm D. McCulloch, 2018. "Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants," Nature Energy, Nature, vol. 3(2), pages 94-101, February.
    9. Zhang, Chenghua & Wu, Jianzhong & Zhou, Yue & Cheng, Meng & Long, Chao, 2018. "Peer-to-Peer energy trading in a Microgrid," Applied Energy, Elsevier, vol. 220(C), pages 1-12.
    10. Zhou, Chenghan & Jia, Hongjie & Jin, Xiaolong & Mu, Yunfei & Yu, Xiaodan & Xu, Xiandong & Li, Binghui & Sun, Weichen, 2023. "Two-stage robust optimization for space heating loads of buildings in integrated community energy systems," Applied Energy, Elsevier, vol. 331(C).
    11. Du, Qiang & Wang, Yalei & Pang, Qiaoyu & Hao, Tingting & Zhou, Yuqing, 2023. "The dynamic analysis on low-carbon building adoption under emission trading scheme," Energy, Elsevier, vol. 263(PC).
    12. Chen, Zheng & Gu, Hongji & Shen, Shiquan & Shen, Jiangwei, 2022. "Energy management strategy for power-split plug-in hybrid electric vehicle based on MPC and double Q-learning," Energy, Elsevier, vol. 245(C).
    13. Sandberg, Nina Holck & Næss, Jan Sandstad & Brattebø, Helge & Andresen, Inger & Gustavsen, Arild, 2021. "Large potentials for energy saving and greenhouse gas emission reductions from large-scale deployment of zero emission building technologies in a national building stock," Energy Policy, Elsevier, vol. 152(C).
    14. Arroyo, Javier & Manna, Carlo & Spiessens, Fred & Helsen, Lieve, 2022. "Reinforced model predictive control (RL-MPC) for building energy management," Applied Energy, Elsevier, vol. 309(C).
    15. Botelho, D.F. & de Oliveira, L.W. & Dias, B.H. & Soares, T.A. & Moraes, C.A., 2022. "Integrated prosumers–DSO approach applied in peer-to-peer energy and reserve tradings considering network constraints," Applied Energy, Elsevier, vol. 317(C).
    16. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(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. Jianhong Hao & Ting Huang & Yi Sun & Xiangpeng Zhan & Yu Zhang & Peng Wu, 2024. "Optimal Prosumer Operation with Consideration for Bounded Rationality in Peer-to-Peer Energy Trading Systems," Energies, MDPI, vol. 17(7), pages 1-22, April.

    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. Jia, Hongjie & Wang, Xiaoyu & Jin, Xiaolong & Cheng, Lin & Mu, Yunfei & Yu, Xiaodan & Wei, Wei, 2024. "Optimal pricing of integrated community energy system for building prosumers with P2P multi-energy trading," Applied Energy, Elsevier, vol. 365(C).
    2. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    3. Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie & Jiang, Qian & Wang, Xiaoyu, 2021. "Peer-to-Peer energy trading strategy for energy balance service provider (EBSP) considering market elasticity in community microgrid," Applied Energy, Elsevier, vol. 303(C).
    4. Wang, Zibo & Dong, Lei & Shi, Mengjie & Qiao, Ji & Jia, Hongjie & Mu, Yunfei & Pu, Tianjiao, 2023. "Market power modeling and restraint of aggregated prosumers in peer-to-peer energy trading: A game-theoretic approach," Applied Energy, Elsevier, vol. 348(C).
    5. Maarten Wolsink, 2020. "Framing in Renewable Energy Policies: A Glossary," Energies, MDPI, vol. 13(11), pages 1-31, June.
    6. Capper, Timothy & Gorbatcheva, Anna & Mustafa, Mustafa A. & Bahloul, Mohamed & Schwidtal, Jan Marc & Chitchyan, Ruzanna & Andoni, Merlinda & Robu, Valentin & Montakhabi, Mehdi & Scott, Ian J. & Franci, 2022. "Peer-to-peer, community self-consumption, and transactive energy: A systematic literature review of local energy market models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    7. Zhou, Yue & Wu, Jianzhong & Song, Guanyu & Long, Chao, 2020. "Framework design and optimal bidding strategy for ancillary service provision from a peer-to-peer energy trading community," Applied Energy, Elsevier, vol. 278(C).
    8. Meng, Yuan & Qiu, Jing & Zhang, Cuo & Lei, Gang & Zhu, Jianguo, 2024. "A Holistic P2P market for active and reactive energy trading in VPPs considering both financial benefits and network constraints," Applied Energy, Elsevier, vol. 356(C).
    9. Dynge, Marthe Fogstad & Crespo del Granado, Pedro & Hashemipour, Naser & Korpås, Magnus, 2021. "Impact of local electricity markets and peer-to-peer trading on low-voltage grid operations," Applied Energy, Elsevier, vol. 301(C).
    10. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    11. Arnob Das & Susmita Datta Peu & Md. Abdul Mannan Akanda & Abu Reza Md. Towfiqul Islam, 2023. "Peer-to-Peer Energy Trading Pricing Mechanisms: Towards a Comprehensive Analysis of Energy and Network Service Pricing (NSP) Mechanisms to Get Sustainable Enviro-Economical Energy Sector," Energies, MDPI, vol. 16(5), pages 1-27, February.
    12. Gržanić, M. & Capuder, T. & Zhang, N. & Huang, W., 2022. "Prosumers as active market participants: A systematic review of evolution of opportunities, models and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    13. Karim L. Anaya & Michael G. Pollitt, 2021. "How to Procure Flexibility Services within the Electricity Distribution System: Lessons from an International Review of Innovation Projects," Energies, MDPI, vol. 14(15), pages 1-26, July.
    14. Lyu, Cheng & Jia, Youwei & Xu, Zhao, 2021. "Fully decentralized peer-to-peer energy sharing framework for smart buildings with local battery system and aggregated electric vehicles," Applied Energy, Elsevier, vol. 299(C).
    15. Wang, Juan & Zheng, Junjun & Yu, Liukai & Goh, Mark & Tang, Yunying & Huang, Yongchao, 2023. "Distributed Reputation-Distance iterative auction system for Peer-To-Peer power trading," Applied Energy, Elsevier, vol. 345(C).
    16. Yang, Yuyan & Xu, Xiao & Pan, Li & Liu, Junyong & Liu, Jichun & Hu, Weihao, 2024. "Distributed prosumer trading in the electricity and carbon markets considering user utility," Renewable Energy, Elsevier, vol. 228(C).
    17. Hutty, Timothy D. & Brown, Solomon, 2024. "P2P trading of heat and power via a continuous double auction," Applied Energy, Elsevier, vol. 369(C).
    18. Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie, 2020. "A distributed Peer-to-Peer energy transaction method for diversified prosumers in Urban Community Microgrid System," Applied Energy, Elsevier, vol. 260(C).
    19. Yaxin Tan & Zhiyu Xu & Weisheng Xu, 2022. "A Two-Phase Hybrid Trading of Green Certificate under Renewables Portfolio Standards in Community of Active Energy Agents," Energies, MDPI, vol. 15(19), pages 1-17, September.
    20. Hu, Qian & Zhu, Ziqing & Bu, Siqi & Wing Chan, Ka & Li, Fangxing, 2021. "A multi-market nanogrid P2P energy and ancillary service trading paradigm: Mechanisms and implementations," Applied Energy, Elsevier, vol. 293(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:359:y:2024:i:c:s0306261924001065. 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.