IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v331y2023ics0306261922015392.html
   My bibliography  Save this article

Distributed tri-layer risk-averse stochastic game approach for energy trading among multi-energy microgrids

Author

Listed:
  • Li, Zhengmao
  • Wu, Lei
  • Xu, Yan
  • Wang, Luhao
  • Yang, Nan

Abstract

This paper discusses a tri-layer non-cooperative energy trading approach among multiple grid-tied multi-energy microgrids (MEMGs) in the restructured integrated energy market. The heterogeneous uncertainties from renewable energy, market prices, and electric energy loads are also considered via the risk-averse stochastic programming (SP) approach. First, comprehensive operation models of individual MEMGs are presented with the consideration of practical electric energy and thermal network flows as well as battery degradation. Second, to guarantee fair multi-energy trading among MEMGs and deal with adverse effects from all uncertainty sources, a tri-layer Cournot Nash game-based energy bidding method is developed and solved by the SP approach. In the first layer, i.e., day-ahead multi-energy market, optimal energy bids, dispatches of energy storage assets, and thermal flows against uncertainty scenarios are acquired in a risk-averse manner; In the second layer, i.e., intra-day multi-energy market, optimal intra-day energy bids and dispatches of all resources against uncertainty realizations are sequentially calculated; In the third layer, i.e., the real-time multi-energy market, transactions between each MEMG and the wholesale multi-energy market are finalized. Third, for protecting the privacy of individual MEMGs and alleviating the computation burdens, the distributed alternating search procedure is employed to compute the Nash equilibriums in the day-ahead and intra-day markets. In the end, numerical case studies are conducted to verify the effectiveness of our method. From the simulation results, it can be inferred that compared with the traditional cooperative, deterministic and risk-natural methods in the literature, our proposed method is more practical and economical for real-world applications since it comprehensively considers the market competition, uncertainty handling, and energy trading risk.

Suggested Citation

  • Li, Zhengmao & Wu, Lei & Xu, Yan & Wang, Luhao & Yang, Nan, 2023. "Distributed tri-layer risk-averse stochastic game approach for energy trading among multi-energy microgrids," Applied Energy, Elsevier, vol. 331(C).
    • Handle: RePEc:eee:appene:v:331:y:2023:i:c:s0306261922015392
    DOI: 10.1016/j.apenergy.2022.120282
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922015392
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.120282?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. Li, Zhengmao & Xu, Yan, 2018. "Optimal coordinated energy dispatch of a multi-energy microgrid in grid-connected and islanded modes," Applied Energy, Elsevier, vol. 210(C), pages 974-986.
    2. Erol, Özge & Başaran Filik, Ümmühan, 2022. "A Stackelberg game approach for energy sharing management of a microgrid providing flexibility to entities," Applied Energy, Elsevier, vol. 316(C).
    3. Mei, Jie & Chen, Chen & Wang, Jianhui & Kirtley, James L., 2019. "Coalitional game theory based local power exchange algorithm for networked microgrids," Applied Energy, Elsevier, vol. 239(C), pages 133-141.
    4. 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).
    5. Bhatti, Bilal Ahmad & Broadwater, Robert, 2020. "Distributed Nash Equilibrium Seeking for a Dynamic Micro-grid Energy Trading Game with Non-quadratic Payoffs," Energy, Elsevier, vol. 202(C).
    6. Karasu, Seçkin & Altan, Aytaç & Bekiros, Stelios & Ahmad, Wasim, 2020. "A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series," Energy, Elsevier, vol. 212(C).
    7. Karasu, Seçkin & Altan, Aytaç, 2022. "Crude oil time series prediction model based on LSTM network with chaotic Henry gas solubility optimization," Energy, Elsevier, vol. 242(C).
    8. Du, Yan & Wang, Zhiwei & Liu, Guangyi & Chen, Xi & Yuan, Haoyu & Wei, Yanli & Li, Fangxing, 2018. "A cooperative game approach for coordinating multi-microgrid operation within distribution systems," Applied Energy, Elsevier, vol. 222(C), pages 383-395.
    9. Oskouei, Morteza Zare & Mohammadi-Ivatloo, Behnam & Abapour, Mehdi & Shafiee, Mahmood & Anvari-Moghaddam, Amjad, 2021. "Privacy-preserving mechanism for collaborative operation of high-renewable power systems and industrial energy hubs," Applied Energy, Elsevier, vol. 283(C).
    10. Wei, Chun & Shen, Zhuzheng & Xiao, Dongliang & Wang, Licheng & Bai, Xiaoqing & Chen, Haoyong, 2021. "An optimal scheduling strategy for peer-to-peer trading in interconnected microgrids based on RO and Nash bargaining," 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. Chunxia Gao & Zhaoyan Zhang & Peiguang Wang, 2023. "Day-Ahead Scheduling Strategy Optimization of Electric–Thermal Integrated Energy System to Improve the Proportion of New Energy," Energies, MDPI, vol. 16(9), pages 1-30, April.
    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. Tan, Bifei & Lin, Zhenjia & Zheng, Xiaodong & Xiao, Fu & Wu, Qiuwei & Yan, Jinyue, 2023. "Distributionally robust energy management for multi-microgrids with grid-interactive EVs considering the multi-period coupling effect of user behaviors," Applied Energy, Elsevier, vol. 350(C).
    4. Zhao, Leilei & Xue, Yixun & Sun, Hongbin & Du, Yuan & Chang, Xinyue & Su, Jia & Li, Zening, 2023. "Benefit allocation for combined heat and power dispatch considering mutual trust," Applied Energy, Elsevier, vol. 345(C).
    5. Yang, Yesen & Li, Zhengmao & Mandapaka, Pradeep V. & Lo, Edmond Y.M., 2023. "Risk-averse restoration of coupled power and water systems with small pumped-hydro storage and stochastic rooftop renewables," Applied Energy, Elsevier, vol. 339(C).
    6. Yantao Wang & Yinhan Zhang & Xuesong Qi & Meiqi Wang & Xinyue Wang, 2023. "A Bi-Level Optimization Model for Virtual Power Plant Membership Selection Considering Load Time Series," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    7. Zheng, Weiye & Lu, Hao & Zhu, Jizhong, 2023. "Incentivizing cooperative electricity-heat operation: A distributed asymmetric Nash bargaining mechanism," Energy, Elsevier, vol. 280(C).
    8. Li, Zhengmao & Xu, Yan & Wang, Peng & Xiao, Gaoxi, 2023. "Coordinated preparation and recovery of a post-disaster Multi-energy distribution system considering thermal inertia and diverse uncertainties," Applied Energy, Elsevier, vol. 336(C).
    9. Shao, Zhentong & Cao, Xiaoyu & Zhai, Qiaozhu & Guan, Xiaohong, 2023. "Risk-constrained planning of rural-area hydrogen-based microgrid considering multiscale and multi-energy storage systems," Applied Energy, Elsevier, vol. 334(C).
    10. Erdong Zhao & Jianmin Chen & Junmei Lan & Liwei Liu, 2024. "Power Generation Mix Optimization under Auction Mechanism for Carbon Emission Rights," Energies, MDPI, vol. 17(3), pages 1-24, January.
    11. Zhou, Siyu & Han, Yang & Mahmoud, Karar & Darwish, Mohamed M.F. & Lehtonen, Matti & Yang, Ping & Zalhaf, Amr S., 2023. "A novel unified planning model for distributed generation and electric vehicle charging station considering multi-uncertainties and battery degradation," Applied Energy, Elsevier, vol. 348(C).
    12. Liang, Weikun & Lin, Shunjiang & Liu, Mingbo & Sheng, Xuan & Pan, Yue & Liu, Yun, 2023. "Risk assessment for cascading failures in regional integrated energy system considering the pipeline dynamics," Energy, Elsevier, vol. 270(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, Xuejie & zhao, Huiru & Lu, Hao & Zhang, Yuanyuan & Wang, Yuwei & Wang, Jingbo, 2022. "Decentralized coordinated operation model of VPP and P2H systems based on stochastic-bargaining game considering multiple uncertainties and carbon cost," Applied Energy, Elsevier, vol. 312(C).
    2. Fioriti, Davide & Frangioni, Antonio & Poli, Davide, 2021. "Optimal sizing of energy communities with fair revenue sharing and exit clauses: Value, role and business model of aggregators and users," Applied Energy, Elsevier, vol. 299(C).
    3. Yu, Xihong & Bao, Han & Chen, Mo & Bao, Bocheng, 2023. "Energy balance via memristor synapse in Morris-Lecar two-neuron network with FPGA implementation," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    4. Wu, Chuantao & Zhou, Dezhi & Lin, Xiangning & Sui, Quan & Wei, Fanrong & Li, Zhengtian, 2022. "A novel energy cooperation framework for multi-island microgrids based on marine mobile energy storage systems," Energy, Elsevier, vol. 252(C).
    5. Mahdi Azimian & Vahid Amir & Reza Habibifar & Hessam Golmohamadi, 2021. "Probabilistic Optimization of Networked Multi-Carrier Microgrids to Enhance Resilience Leveraging Demand Response Programs," Sustainability, MDPI, vol. 13(11), pages 1-30, May.
    6. Shabani, Masoume & Wallin, Fredrik & Dahlquist, Erik & Yan, Jinyue, 2022. "Techno-economic assessment of battery storage integrated into a grid-connected and solar-powered residential building under different battery ageing models," Applied Energy, Elsevier, vol. 318(C).
    7. Lian, Yicheng & Li, Yuanzheng & Zhao, Yong & Yu, Chaofan & Zhao, Tianyang & Wu, Lei, 2023. "Robust multi-objective optimization for islanded data center microgrid operations," Applied Energy, Elsevier, vol. 330(PB).
    8. Yao, Qijia & Alsaade, Fawaz W. & Al-zahrani, Mohammed S. & Jahanshahi, Hadi, 2023. "Fixed-time neural control for output-constrained synchronization of second-order chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    9. Tian, Di & Qu, Zhiguo & Zhang, Jianfei, 2023. "Electrochemical condition optimization and techno-economic analysis on the direct CO2 electroreduction of flue gas," Applied Energy, Elsevier, vol. 351(C).
    10. Filipe Bandeiras & Álvaro Gomes & Mário Gomes & Paulo Coelho, 2023. "Application and Challenges of Coalitional Game Theory in Power Systems for Sustainable Energy Trading Communities," Energies, MDPI, vol. 16(24), pages 1-42, December.
    11. Qiu, Dawei & Wang, Yi & Zhang, Tingqi & Sun, Mingyang & Strbac, Goran, 2023. "Hierarchical multi-agent reinforcement learning for repair crews dispatch control towards multi-energy microgrid resilience," Applied Energy, Elsevier, vol. 336(C).
    12. Han, Dongho & Lee, Jay H., 2021. "Two-stage stochastic programming formulation for optimal design and operation of multi-microgrid system using data-based modeling of renewable energy sources," Applied Energy, Elsevier, vol. 291(C).
    13. Kanakadhurga, Dharmaraj & Prabaharan, Natarajan, 2022. "Peer-to-Peer trading with Demand Response using proposed smart bidding strategy," Applied Energy, Elsevier, vol. 327(C).
    14. Fina, Bernadette & Auer, Hans & Friedl, Werner, 2019. "Profitability of PV sharing in energy communities: Use cases for different settlement patterns," Energy, Elsevier, vol. 189(C).
    15. Wang, Xuejie & Li, Bingkang & Wang, Yuwei & Lu, Hao & Zhao, Huiru & Xue, Wanlei, 2022. "A bargaining game-based profit allocation method for the wind-hydrogen-storage combined system," Applied Energy, Elsevier, vol. 310(C).
    16. Yu, Chuanjin & Li, Yongle & Chen, Qian & Lai, Xiaopan & Zhao, Liyang, 2022. "Matrix-based wavelet transformation embedded in recurrent neural networks for wind speed prediction," Applied Energy, Elsevier, vol. 324(C).
    17. Li, Fuxiang & Wu, Wei, 2022. "Coupled electrical-thermal performance estimation of photovoltaic devices: A transient multiphysics framework with robust parameter extraction and 3-D thermal analysis," Applied Energy, Elsevier, vol. 319(C).
    18. Shi, Changfeng & Zhi, Jiaqi & Yao, Xiao & Zhang, Hong & Yu, Yue & Zeng, Qingshun & Li, Luji & Zhang, Yuxi, 2023. "How can China achieve the 2030 carbon peak goal—a crossover analysis based on low-carbon economics and deep learning," Energy, Elsevier, vol. 269(C).
    19. Qian, Jiaxin & Wu, Jiahui & Yao, Lei & Mahmut, Saniye & Zhang, Qiang, 2021. "Comprehensive performance evaluation of Wind-Solar-CCHP system based on emergy analysis and multi-objective decision method," Energy, Elsevier, vol. 230(C).
    20. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.

    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:331:y:2023:i:c:s0306261922015392. 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.