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Tri-layer low-carbon distributed optimization of IES based on hybrid games under stochastic scenarios
  • +3
  • Ziyi Yue,
  • Huazhi Liu,
  • Yonggang LI,
  • Yuyao Zhong,
  • Jiachen Yao,
  • Yuxuan Li
Ziyi Yue
North China Electric Power University - Baoding Campus
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Huazhi Liu
State Grid Tianjin Economic Research Institute
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Yonggang LI
North China Electric Power University

Corresponding Author:lygzxm0@163.com

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Yuyao Zhong
North China Electric Power University - Baoding Campus
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Jiachen Yao
Jibei Chengde Power Supply Company Chengde County Power Supply Branch Company
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Yuxuan Li
North China Electric Power University - Baoding Campus
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Abstract

Low-carbon development of integrated energy systems is achieved via the sharing of multiple energy interactions by park-level integrated energy systems (PIESs). However, coordinating profit distribution conflict between complex interactive stakeholders under stochastic scenarios is challenging. Accordingly, this study proposes a novel tri-layer framework that aggregates different game mechanisms to investigate the interactions between PIESs and coupled energy markets. First, a linkage trading mechanism is proposed by integrating carbon emissions trading and green certificate trading , which establishes a coupled electricity-carbon-green certificate market. Consequently, a park aggregation operator acts as an intermediary between PIESs and the coupled market, setting purchase and sale prices to guide unit generation in each PIES using the master-slave game theory. Then, the Nash game theory is applied to realize a cooperative bargaining among PIESs for fair revenue distribution. Further, the impact of uncertain environments has been considered using stochastic scenario methods and the conditional value-at-risk theory. Furthermore, to protect the privacy of each participating agent while improving convergence speed, a differential evolutionary method is combined with analysis target cascading to solve the framework. Finally, the proposed scheduling method is verified using a typical case to optimize conflicting PIES interests in multiple scenarios and realize decarbonization transformation.
15 Jul 2023Submitted to IET Generation, Transmission & Distribution
19 Jul 2023Submission Checks Completed
19 Jul 2023Assigned to Editor
04 Aug 2023Reviewer(s) Assigned
28 Aug 2023Review(s) Completed, Editorial Evaluation Pending
29 Aug 2023Editorial Decision: Revise Major
15 Sep 20231st Revision Received
18 Sep 2023Submission Checks Completed
18 Sep 2023Assigned to Editor
18 Sep 2023Review(s) Completed, Editorial Evaluation Pending
18 Sep 2023Reviewer(s) Assigned
28 Sep 2023Editorial Decision: Accept