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Economic-emission dispatch problem in integrated electricity and heat system considering multi-energy demand response and carbon capture Technologies

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  • Yang, Dongfeng
  • Xu, Yang
  • Liu, Xiaojun
  • Jiang, Chao
  • Nie, Fanjie
  • Ran, Zixu

Abstract

To combat global warming caused by excessive CO2 emissions, it is critical to achieving low-carbon economic operation of integrated electricity and heat systems (IEHS). Thermal power plants with carbon capture systems can significantly reduce the spread of carbon emissions, thus effectively reducing the overall carbon footprint. Meanwhile, the development and utilization of renewable energy sources, such as wind power, can effectively limit overall carbon emissions. Hence, this paper proposes a multi-objective optimization scheme incorporating carbon capture power plants (CCPP) and multi-energy demand response (MEDR), considering the uncertainties of the system for the economic-emission dispatch problem in IEHS. First, the energy flow mechanism and analysis of the wind power abandonment of the IEHS are presented. Then, the low-carbon mechanisms of the MEDR and CCPP are investigated. The uncertainties of the system are described by a membership function to ensure the reserve requirements. A weight setting method based on the improved analytic hierarchy process method is proposed, in which the multi-objective function is transformed into a single-objective function. The case studies were tested on an improved IEEE-30 bus power system and a 6-bus district heating system. The results demonstrate the effectiveness of the proposed method in reducing carbon emissions and improving wind power consumption.

Suggested Citation

  • Yang, Dongfeng & Xu, Yang & Liu, Xiaojun & Jiang, Chao & Nie, Fanjie & Ran, Zixu, 2022. "Economic-emission dispatch problem in integrated electricity and heat system considering multi-energy demand response and carbon capture Technologies," Energy, Elsevier, vol. 253(C).
    • Handle: RePEc:eee:energy:v:253:y:2022:i:c:s0360544222010568
    DOI: 10.1016/j.energy.2022.124153
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    4. Yang, Xiaohui & Zhang, Zhonglian & Mei, Linghao & Wang, Xiaopeng & Deng, Yeheng & Wei, Shi & Liu, Xiaoping, 2023. "Optimal configuration of improved integrated energy system based on stepped carbon penalty response and improved power to gas," Energy, Elsevier, vol. 263(PD).
    5. Zhang, Bin & Wu, Xuewei & Ghias, Amer M.Y.M. & Chen, Zhe, 2023. "Coordinated carbon capture systems and power-to-gas dynamic economic energy dispatch strategy for electricity–gas coupled systems considering system uncertainty: An improved soft actor–critic approach," Energy, Elsevier, vol. 271(C).
    6. 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).
    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. Yuxing Liu & Linjun Zeng & Jie Zeng & Zhenyi Yang & Na Li & Yuxin Li, 2023. "Scheduling Optimization of IEHS with Uncertainty of Wind Power and Operation Mode of CCP," Energies, MDPI, vol. 16(5), pages 1-17, February.
    9. Wang, Yajun & Wang, Jidong & Cao, Man & Kong, Xiangyu & Abderrahim, Bouchedjira & Yuan, Long & Vartosh, Aris, 2023. "Dynamic emission dispatch considering the probabilistic model with multiple smart energy system players based on a developed fuzzy theory-based harmony search algorithm," Energy, Elsevier, vol. 269(C).
    10. Chenhui Xu & Yunkai Huang, 2023. "Integrated Demand Response in Multi-Energy Microgrids: A Deep Reinforcement Learning-Based Approach," Energies, MDPI, vol. 16(12), pages 1-19, June.

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