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Multi-Objective Co-Operative Game-Based Optimization for Park-Level Integrated Energy System Based on Exergy-Economic Analysis

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  • Lili Mo

    (Architectural Design Research Institute of SCUT, South China University of Technology, Guangzhou 510000, China
    School of Electric Power, South China University of Technology, Guangzhou 510641, China)

  • Zeyu Deng

    (School of Electric Power, South China University of Technology, Guangzhou 510641, China)

  • Haoyong Chen

    (School of Electric Power, South China University of Technology, Guangzhou 510641, China)

  • Junkun Lan

    (School of Electric Power, South China University of Technology, Guangzhou 510641, China)

Abstract

The park-level integrated energy system (PIES) can realize the gradient utilization of energy and improve the efficiency of energy utilization through the coupling between multiple types of energy sub-networks. However, energy analysis and exergy analysis cannot be used to evaluate the economics of PIES. In addition, conflicts of interest among integrated energy suppliers make the economic scheduling of the PIES more difficult. In this paper, we propose a multi-objective collaborative game-based optimization method based on exergy economics, in which the introduction of exergy economics realizes the economic assessment of any link within the PIES, and the optimization model constructed based on the potential game solves the problem of conflict of interest among multiple energy suppliers and improves the benefits of each supplier. Finally, taking a PIES in Guangzhou as an example, the rationality of the optimization scheme proposed in this paper is demonstrated by comparing it with the classical optimization scheme.

Suggested Citation

  • Lili Mo & Zeyu Deng & Haoyong Chen & Junkun Lan, 2023. "Multi-Objective Co-Operative Game-Based Optimization for Park-Level Integrated Energy System Based on Exergy-Economic Analysis," Energies, MDPI, vol. 16(24), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:7945-:d:1295656
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    References listed on IDEAS

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    1. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Tsatsaronis, Georgios & Winhold, Michael, 1985. "Exergoeconomic analysis and evaluation of energy-conversion plants—I. A new general methodology," Energy, Elsevier, vol. 10(1), pages 69-80.
    3. Wang, Yongli & Liu, Zhen & Cai, Chengcong & Xue, Lu & Ma, Yang & Shen, Hekun & Chen, Xin & Liu, Lin, 2022. "Research on the optimization method of integrated energy system operation with multi-subject game," Energy, Elsevier, vol. 245(C).
    4. Duan, Pengfei & Zhao, Bingxu & Zhang, Xinghui & Fen, Mengdan, 2023. "A day-ahead optimal operation strategy for integrated energy systems in multi-public buildings based on cooperative game," Energy, Elsevier, vol. 275(C).
    5. Ma, Kai & Zhang, Rencai & Yang, Jie & Song, Debao, 2023. "Collaborative optimization scheduling of integrated energy system considering user dissatisfaction," Energy, Elsevier, vol. 274(C).
    6. 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).
    7. Frangopoulos, Christos A., 2018. "Recent developments and trends in optimization of energy systems," Energy, Elsevier, vol. 164(C), pages 1011-1020.
    8. Wang, Shouxiang & Wang, Shaomin & Zhao, Qianyu & Dong, Shuai & Li, Hao, 2023. "Optimal dispatch of integrated energy station considering carbon capture and hydrogen demand," Energy, Elsevier, vol. 269(C).
    9. Hu, Zhengbiao & He, Dongfeng & Zhao, Hongbo, 2023. "Multi-objective optimization of energy distribution in steel enterprises considering both exergy efficiency and energy cost," Energy, Elsevier, vol. 263(PB).
    10. Jiang, Tao & Zhang, Rufeng & Li, Xue & Chen, Houhe & Li, Guoqing, 2021. "Integrated energy system security region: Concepts, methods, and implementations," Applied Energy, Elsevier, vol. 283(C).
    11. Wang, Jiangjiang & Lu, Zherui & Li, Meng & Lior, Noam & Li, Weihua, 2019. "Energy, exergy, exergoeconomic and environmental (4E) analysis of a distributed generation solar-assisted CCHP (combined cooling, heating and power) gas turbine system," Energy, Elsevier, vol. 175(C), pages 1246-1258.
    12. Yan Xiong & Jiakun Fang, 2022. "Co-Operative Optimization Framework for Energy Management Considering CVaR Assessment and Game Theory," Energies, MDPI, vol. 15(24), pages 1-17, December.
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