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Research on Low-Carbon Energy Sharing through the Alliance of Integrated Energy Systems with Multiple Uncertainties

Author

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  • Zhihan Shi

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

  • Weisong Han

    (College of Transportation Engineering, Nanjing Tech University, Nanjing 211899, China)

  • Guangming Zhang

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

  • Zhiqing Bai

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

  • Mingxiang Zhu

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China
    Taizhou College, Nanjing Normal University, Taizhou 225300, China)

  • Xiaodong Lv

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

Abstract

It is of great significance to introduce the conception of a sharing economy into the electricity industry, which can promote the dispatch of multiple integrated energy systems. On the one hand, it is difficult to reveal the behaviors of complex players with multi-energy coupling through the traditional centralized optimization method of single electric energy. On the other hand, the uncertain fluctuations of renewable energy, such as wind power and photovoltaic, have posed great challenges to market transactions. First, the relationship and the functions of all stakeholders in the system are described in this paper, followed by the establishment of flexible resource models such as demand response and energy storage devices. On this basis, a low-carbon dispatching framework of multiple regional gas–electric integrated energy systems is then constructed under the guidance of cooperative game theory. The contribution indexes are established to measure the degree of energy sharing among the subsystems, and the method of asymmetric Nash bargaining is used to settle the interests of each subsystem. Second, a robust optimization model of multiple regional systems is established in response to multiple uncertainties from renewable energy and load. Finally, the numerical example proves that the proposed mechanism can increase the benefits of each integrated energy system player. Moreover, it helps the system to yield optimal benefits in the face of uncertainties and provides a reference on how to realize energy sharing under uncertainties from source load.

Suggested Citation

  • Zhihan Shi & Weisong Han & Guangming Zhang & Zhiqing Bai & Mingxiang Zhu & Xiaodong Lv, 2022. "Research on Low-Carbon Energy Sharing through the Alliance of Integrated Energy Systems with Multiple Uncertainties," Energies, MDPI, vol. 15(24), pages 1-20, December.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9604-:d:1007021
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    References listed on IDEAS

    as
    1. Alabi, Tobi Michael & Lu, Lin & Yang, Zaiyue, 2022. "Data-driven optimal scheduling of multi-energy system virtual power plant (MEVPP) incorporating carbon capture system (CCS), electric vehicle flexibility, and clean energy marketer (CEM) strategy," Applied Energy, Elsevier, vol. 314(C).
    2. Hong, Bowen & Zhang, Weitong & Zhou, Yue & Chen, Jian & Xiang, Yue & Mu, Yunfei, 2018. "Energy-Internet-oriented microgrid energy management system architecture and its application in China," Applied Energy, Elsevier, vol. 228(C), pages 2153-2164.
    3. Gholami, M. & Sanjari, M.J., 2021. "Multiobjective energy management in battery-integrated home energy systems," Renewable Energy, Elsevier, vol. 177(C), pages 967-975.
    4. Zhengjie Li & Zhisheng Zhang, 2021. "Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting," Energies, MDPI, vol. 14(9), pages 1-14, April.
    5. Tengfei Ma & Junyong Wu & Liangliang Hao & Huaguang Yan & Dezhi Li, 2018. "A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach," Energies, MDPI, vol. 11(10), pages 1-19, October.
    6. Cheng, Ying & Liu, Mingbo & Chen, Honglin & Yang, Ziwei, 2021. "Optimization of multi-carrier energy system based on new operation mechanism modelling of power-to-gas integrated with CO2-based electrothermal energy storage," Energy, Elsevier, vol. 216(C).
    7. Tushar, Wayes & Saha, Tapan Kumar & Yuen, Chau & Morstyn, Thomas & McCulloch, Malcolm D. & Poor, H. Vincent & Wood, Kristin L., 2019. "A motivational game-theoretic approach for peer-to-peer energy trading in the smart grid," Applied Energy, Elsevier, vol. 243(C), pages 10-20.
    8. Liu, Zhiqiang & Cui, Yanping & Wang, Jiaqiang & Yue, Chang & Agbodjan, Yawovi Souley & Yang, Yu, 2022. "Multi-objective optimization of multi-energy complementary integrated energy systems considering load prediction and renewable energy production uncertainties," Energy, Elsevier, vol. 254(PC).
    9. Chen, Cong & Sun, Hongbin & Shen, Xinwei & Guo, Ye & Guo, Qinglai & Xia, Tian, 2019. "Two-stage robust planning-operation co-optimization of energy hub considering precise energy storage economic model," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    10. Zhou, Yuqi & Yu, Wenbin & Zhu, Shanying & Yang, Bo & He, Jianping, 2021. "Distributionally robust chance-constrained energy management of an integrated retailer in the multi-energy market," Applied Energy, Elsevier, vol. 286(C).
    11. Huang, Yujing & Wang, Yudong & Liu, Nian, 2022. "A two-stage energy management for heat-electricity integrated energy system considering dynamic pricing of Stackelberg game and operation strategy optimization," Energy, Elsevier, vol. 244(PA).
    12. Oveis Abedinia & Mehdi Bagheri, 2021. "Power Distribution Optimization Based on Demand Respond with Improved Multi-Objective Algorithm in Power System Planning," Energies, MDPI, vol. 14(10), pages 1-18, May.
    13. 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).
    14. Quan, Hao & Srinivasan, Dipti & Khambadkone, Ashwin M. & Khosravi, Abbas, 2015. "A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources," Applied Energy, Elsevier, vol. 152(C), pages 71-82.
    15. Zhong, Junjie & Cao, Yijia & Li, Yong & Tan, Yi & Peng, Yanjian & Cao, Lihua & Zeng, Zilong, 2021. "Distributed modeling considering uncertainties for robust operation of integrated energy system," Energy, Elsevier, vol. 224(C).
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