Cooperative Game-Theoretic Scheduling for Low-Carbon Integrated Energy Systems with P2G–CCS Synergy

Huijia Liu, Sheng Ye (), Chengkai Yin, Lei Wang and Can Zhang
Additional contact information
Huijia Liu: College of Electrical Engineering and New Energy, China Three Gorges University, No. 8 University Road, Yichang 443002, China
Sheng Ye: College of Electrical Engineering and New Energy, China Three Gorges University, No. 8 University Road, Yichang 443002, China
Chengkai Yin: College of Electrical Engineering and New Energy, China Three Gorges University, No. 8 University Road, Yichang 443002, China
Lei Wang: College of Electrical Engineering and New Energy, China Three Gorges University, No. 8 University Road, Yichang 443002, China
Can Zhang: College of Electrical Engineering and New Energy, China Three Gorges University, No. 8 University Road, Yichang 443002, China

Energies, 2025, vol. 18, issue 15, 1-22

Abstract: In the context of the dual-carbon goals, this study proposes a cooperative game-theoretic optimization strategy to enhance the energy utilization efficiency, operational efficiency, and cost-effectiveness of integrated energy systems (IESs) while simultaneously reducing carbon emissions, improving operational flexibility, and mitigating renewable energy variability. To achieve these goals, an IES framework integrating power-to-gas (P2G) technology and carbon capture and storage (CCS) facilities is established to regulate carbon emissions. The system incorporates P2G conversion units and thermal components—specifically, hydrogen fuel cells, electrolyzers, reactors, and electric boilers—aiming to maximize energy conversion efficiency and asset utilization. A cooperative game-theoretic optimization model is developed to facilitate collaboration among multiple stakeholders within the coalition, which employs the Shapley value method to ensure equitable distribution of the cooperative surplus, thereby maximizing collective benefits. The model is solved using an improved gray wolf optimizer (IGWO). The simulation results demonstrate that the proposed strategy effectively coordinates multi-IES scheduling, significantly reduces carbon emissions, facilitates the efficient allocation of cooperation gains, and maximizes overall system utility.

Keywords: IES; cooperative game theory; low-carbon scheduling; Shapley value; IGWO (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/18/15/3942/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/15/3942/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:15:p:3942-:d:1708653

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().