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Strategic behavior modeling and energy management for electric-thermal-carbon-natural gas integrated energy system considering ancillary service

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  • Li, Jiamei
  • Ai, Qian
  • Chen, Minyu

Abstract

Carbon capture system (CCS) and power to gas (P2G), as key low-carbon technologies, have obtained the widespread attention. Thus, it is necessary to explore the operation pattern and benefits of CCS and P2G. This paper investigates their roles in the electric-thermal-carbon-natural gas integrated energy system (IES) and focuses on the multi-market participation and multi-energy management. IES participates in the electricity, carbon trading, and natural gas markets. In the electricity market, IES can provide two types of ancillary services: deep peak regulation and frequency regulation services. Then, owing to the small scale of the ancillary service market, the strategic behaviors of IES are discussed. A bi-level model is established to deal with the complex couplings in the peak regulation market. IES's strategic behavior in the frequency regulation market is depicted by the price quota curve. Next, a solution method based on the particle swarm optimization algorithm is proposed to deal with the nonconvexity of the lower-level model. Finally, case studies show that the strategic behavior modeling in this paper can increase the profits of the deep peak regulation and the frequency regulation services. When IES is equipped with CCS and P2G, the operation cost decreases by 16.6%.

Suggested Citation

  • Li, Jiamei & Ai, Qian & Chen, Minyu, 2023. "Strategic behavior modeling and energy management for electric-thermal-carbon-natural gas integrated energy system considering ancillary service," Energy, Elsevier, vol. 278(C).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:c:s0360544223011398
    DOI: 10.1016/j.energy.2023.127745
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    1. Li, Fei & Wang, Dong & Guo, Hengdao & Liu, Zhan & Zhang, Jianhua & Lin, Zhifang, 2025. "Two-stage Distributionally robust optimization for hydrogen-IES participation in energy-carbon trading-frequency regulation ancillary services market," Energy, Elsevier, vol. 328(C).
    2. Li, Fei & Wang, Dong & Guo, Hengdao & Zhang, Jianhua, 2024. "Distributionally Robust Optimization for integrated energy system accounting for refinement utilization of hydrogen and ladder-type carbon trading mechanism," Applied Energy, Elsevier, vol. 367(C).
    3. Zhu, Xiaoxun & Hu, Ming & Xue, Jinfei & Li, Yuxuan & Han, Zhonghe & Gao, Xiaoxia & Wang, Yu & Bao, Linlin, 2024. "Research on multi-time scale integrated energy scheduling optimization considering carbon constraints," Energy, Elsevier, vol. 302(C).
    4. Du, Yida & Li, Xiangguang & Liang, Yan & Tan, Zhongfu, 2024. "Two-stage multi-objective distributionally robust optimization of the electricity-hydrogen coupling system under multiple markets," Energy, Elsevier, vol. 303(C).
    5. Lin, Xiaojie & Lin, Xueru & Zhong, Wei & Zhou, Yi, 2024. "Multi-time scale dynamic operation optimization method for industrial park electricity-heat-gas integrated energy system considering demand elasticity," Energy, Elsevier, vol. 293(C).
    6. Chen, Shi & Li, Chuangzhi & Zang, Tianlei & Zhou, Buxiang & Yang, Lonjie & Qiu, Yiwei & Zhou, Yi & Zhang, Xiaoshun, 2024. "Multi-timescale dispatch technology for islanded energy system in the Gobi Desert," Renewable Energy, Elsevier, vol. 234(C).
    7. Xin Huang & Junjie Zhong & Maner Xiao & Yuhui Zhu & Haojie Zheng & Bensheng Zheng, 2025. "Optimal and Sustainable Scheduling of Integrated Energy System Coupled with CCS-P2G and Waste-to-Energy Under the “Green-Carbon” Offset Mechanism," Sustainability, MDPI, vol. 17(11), pages 1-27, May.

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