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Research on day-ahead transactions between multi-microgrid based on cooperative game model

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  • Chen, Weidong
  • Wang, Junnan
  • Yu, Guanyi
  • Chen, Jiajia
  • Hu, Yumeng

Abstract

Microgrids are one of the most common forms of distributed energy participation in the electricity market. This paper discusses the lack of market competition among independent microgrids as a factor in setting up a cooperative alliance among microgrids. Independent microgrids aim to minimize the system's overall operating costs. The first principle is to maximize scenery output and consumption. We develop and solve an optimization model to obtain the interactive power with the distribution network and the charging and discharging power arrangement for the energy storage module. We then construct a cooperative game model among multiple microgrids on this basis. Nash bargaining is used to coordinate the distribution of benefits among microgrids, as well as to analyze the optimal trading power and tariffs among microgrids. The research proves that the cooperative game among microgrids can realize the flexible consumption of renewable energy in the region. Microgrids also have lower operating costs. The Nash bargaining helps the members in the coalition to get satisfactory trading power and tariff. Additionally, it effectively improves the overall operational efficiency and market competitiveness of microgrid systems.

Suggested Citation

  • Chen, Weidong & Wang, Junnan & Yu, Guanyi & Chen, Jiajia & Hu, Yumeng, 2022. "Research on day-ahead transactions between multi-microgrid based on cooperative game model," Applied Energy, Elsevier, vol. 316(C).
    • Handle: RePEc:eee:appene:v:316:y:2022:i:c:s0306261922004913
    DOI: 10.1016/j.apenergy.2022.119106
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    as
    1. Karimi, Hamid & Jadid, Shahram, 2019. "Optimal microgrid operation scheduling by a novel hybrid multi-objective and multi-attribute decision-making framework," Energy, Elsevier, vol. 186(C).
    2. Hotaling, Chelsea & Bird, Stephen & Heintzelman, Martin D., 2021. "Willingness to pay for microgrids to enhance community resilience," Energy Policy, Elsevier, vol. 154(C).
    3. Roslan, M.F. & Hannan, M.A. & Jern Ker, Pin & Begum, R.A. & Indra Mahlia, TM & Dong, Z.Y., 2021. "Scheduling controller for microgrids energy management system using optimization algorithm in achieving cost saving and emission reduction," Applied Energy, Elsevier, vol. 292(C).
    4. Hu, Mian & Wang, Yan-Wu & Xiao, Jiang-Wen & Lin, Xiangning, 2019. "Multi-energy management with hierarchical distributed multi-scale strategy for pelagic islanded microgrid clusters," Energy, Elsevier, vol. 185(C), pages 910-921.
    5. 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.
    6. 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.
    7. Rodríguez, Fermín & Fleetwood, Alice & Galarza, Ainhoa & Fontán, Luis, 2018. "Predicting solar energy generation through artificial neural networks using weather forecasts for microgrid control," Renewable Energy, Elsevier, vol. 126(C), pages 855-864.
    8. Oussama Ouramdane & Elhoussin Elbouchikhi & Yassine Amirat & Ehsan Sedgh Gooya, 2021. "Optimal Sizing and Energy Management of Microgrids with Vehicle-to-Grid Technology: A Critical Review and Future Trends," Energies, MDPI, vol. 14(14), pages 1-45, July.
    9. Mengelkamp, Esther & Gärttner, Johannes & Rock, Kerstin & Kessler, Scott & Orsini, Lawrence & Weinhardt, Christof, 2018. "Designing microgrid energy markets," Applied Energy, Elsevier, vol. 210(C), pages 870-880.
    10. Karimi, Hamid & Jadid, Shahram, 2020. "Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework," Energy, Elsevier, vol. 195(C).
    11. Cagnano, A. & De Tuglie, E. & Mancarella, P., 2020. "Microgrids: Overview and guidelines for practical implementations and operation," Applied Energy, Elsevier, vol. 258(C).
    12. Zhang, Bingying & Li, Qiqiang & Wang, Luhao & Feng, Wei, 2018. "Robust optimization for energy transactions in multi-microgrids under uncertainty," Applied Energy, Elsevier, vol. 217(C), pages 346-360.
    13. Haghi, Ehsan & Raahemifar, Kaamran & Fowler, Michael, 2018. "Investigating the effect of renewable energy incentives and hydrogen storage on advantages of stakeholders in a microgrid," Energy Policy, Elsevier, vol. 113(C), pages 206-222.
    14. Li, Zhengmao & Xu, Yan, 2019. "Temporally-coordinated optimal operation of a multi-energy microgrid under diverse uncertainties," Applied Energy, Elsevier, vol. 240(C), pages 719-729.
    15. Nash, John, 1950. "The Bargaining Problem," Econometrica, Econometric Society, vol. 18(2), pages 155-162, April.
    16. Basu, M., 2021. "Heat and power generation augmentation planning of isolated microgrid," Energy, Elsevier, vol. 223(C).
    17. Yang, Qiangda & Dong, Ning & Zhang, Jie, 2021. "An enhanced adaptive bat algorithm for microgrid energy scheduling," Energy, Elsevier, vol. 232(C).
    18. Yin, Linfei & Zhang, Bin, 2021. "Time series generative adversarial network controller for long-term smart generation control of microgrids," Applied Energy, Elsevier, vol. 281(C).
    19. Leonori, Stefano & Martino, Alessio & Frattale Mascioli, Fabio Massimo & Rizzi, Antonello, 2020. "Microgrid Energy Management Systems Design by Computational Intelligence Techniques," Applied Energy, Elsevier, vol. 277(C).
    20. Fossati, Juan P. & Galarza, Ainhoa & Martín-Villate, Ander & Fontán, Luis, 2015. "A method for optimal sizing energy storage systems for microgrids," Renewable Energy, Elsevier, vol. 77(C), pages 539-549.
    Full references (including those not matched with items on IDEAS)

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    4. Wang, L.L. & Xian, R.C. & Jiao, P.H. & Liu, X.H. & Xing, Y.W. & Wang, W., 2024. "Cooperative operation of industrial/commercial/residential integrated energy system with hydrogen energy based on Nash bargaining theory," Energy, Elsevier, vol. 288(C).
    5. Dong, Lei & Zhang, Shiming & Zhang, Tao & Wang, Zibo & Qiao, Ji & Pu, Tianjiao, 2024. "DSO-prosumers dual-layer game optimization based on risk price guidance in a P2P energy market environment," Applied Energy, Elsevier, vol. 361(C).
    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. Rajib Mahamud & Chanwoo Park, 2022. "Theory and Practices of Li-Ion Battery Thermal Management for Electric and Hybrid Electric Vehicles," Energies, MDPI, vol. 15(11), pages 1-45, May.
    8. Liao, Wei & Xiao, Fu & Li, Yanxue & Peng, Jinqing, 2024. "Comparative study on electricity transactions between multi-microgrid: A hybrid game theory-based peer-to-peer trading in heterogeneous building communities considering electric vehicles," Applied Energy, Elsevier, vol. 367(C).
    9. 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).
    10. Yuzhe Xie & Yan Yao & Yawu Wang & Weiqiang Cha & Sheng Zhou & Yue Wu & Chunyi Huang, 2022. "A Cooperative Game-Based Sizing and Configuration of Community-Shared Energy Storage," Energies, MDPI, vol. 15(22), pages 1-17, November.
    11. Zhou, Kaile & Fei, Zhineng & Hu, Rong, 2023. "Hybrid robust decentralized optimization of emission-aware multi-energy microgrids considering multiple uncertainties," Energy, Elsevier, vol. 265(C).
    12. Han, Zhixin & Fang, Debin & Yang, Peiwen & Lei, Leyao, 2023. "Cooperative mechanisms for multi-energy complementarity in the electricity spot market," Energy Economics, Elsevier, vol. 127(PB).
    13. Zhou, Dequn & Zhang, Yining & Wang, Qunwei & Ding, Hao, 2024. "How do uncertain renewable energy induced risks evolve in a two-stage deregulated wholesale power market," Applied Energy, Elsevier, vol. 353(PB).
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    15. Jani, Ali & Jadid, Shahram, 2023. "Two-stage energy scheduling framework for multi-microgrid system in market environment," Applied Energy, Elsevier, vol. 336(C).
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