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Research on multi-energy collaborative operation optimization of integrated energy system considering carbon trading and demand response

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  • Yang, Meng
  • Liu, Yisheng

Abstract

Integrated energy systems (IES) have been applied to raise the efficiency of energy utilization and facilitate the sustainable transition of society and energy system. To further explore the multi-energy coupling capacity and carbon reduction potential of the IESs, this study proposes a cooling-heat-electricity-gas collaborative optimization model of IES given ladder carbon trading (LCT) mechanism and multi-energy demand response (MDR). To begin with, the MDR model is developed following the demand characteristics of the system. Given the incentive effect of the LCT on the low-carbon performance of the IESs, the multi-energy coupling low-carbon operation optimization model is proposed. By constructing four application scenarios, the proposed model is practiced in investigating the performance of IES across various market mechanisms. The simulation findings indicate the introduction of the LCT cuts the carbon emissions of the IES by approximately 6.7%, and the MDR mechanism effectively optimizes the energy use curve by regulating user behavior. The combined consideration of the two market mechanisms saves around 9.21% of the IES's operation cost and strengthens the performance of IES towards the green and economic operation. The carbon market requires rational prices to inspire IES. The proposed model offers a significant benchmark for the IES's green performance optimization.

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  • Yang, Meng & Liu, Yisheng, 2023. "Research on multi-energy collaborative operation optimization of integrated energy system considering carbon trading and demand response," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223025112
    DOI: 10.1016/j.energy.2023.129117
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    2. Jiang, Meihui & Xu, Zhenjiang & Zhu, Hongyu & Hwang Goh, Hui & Agustiono Kurniawan, Tonni & Liu, Tianhao & Zhang, Dongdong, 2024. "Integrated demand response modeling and optimization technologies supporting energy internet," Renewable and Sustainable Energy Reviews, Elsevier, vol. 203(C).
    3. Cui, Jia & Zhang, Ximing & Liu, Wei & Yan, Xinyue & Hu, Zhen & Li, Chaoran & Huang, Jingbo, 2024. "A novel trading optimization strategy of source-load bilateral thermoelectric spot based on industrial parks interior," Energy, Elsevier, vol. 302(C).
    4. Chen, Yuzhu & Guo, Weimin & Du, Na & Yang, Kun & Wang, Jiangjiang, 2024. "Master slave game-based optimization of an off-grid combined cooling and power system coupled with solar thermal and photovoltaics considering carbon cost allocation," Renewable Energy, Elsevier, vol. 229(C).
    5. Zhao, Wenna & Ma, Kai & Yang, Jie & Guo, Shiliang, 2024. "A multi-time scale demand response scheme based on noncooperative game for economic operation of industrial park," Energy, Elsevier, vol. 302(C).

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