Game-Theoretic Hierarchical Optimization of Electricity–Heat–Hydrogen Energy Systems with Carbon Capture

The coupling of electricity, heat, and hydrogen subsystems together with carbon capture technologies introduces complex operational interactions in modern multi-energy systems. Existing game-based scheduling studies mainly focus on electricity–heat or electricity–heat–gas coupling, often neglecting hydrogen blending, carbon capture integration, and strategic coordination among heterogeneous stakeholders. To address these gaps, this study develops a game-theoretic hierarchical optimization framework for electricity–heat–hydrogen integrated energy systems incorporating carbon capture. Compared with conventional multi-energy game models, the proposed framework integrates hydrogen blending and carbon capture into a unified electricity–heat–hydrogen–carbon coupling structure, enabling coordinated low-carbon operation. A Stackelberg leader–follower structure is adopted, where the upper-level operator determines electricity and heat prices, and lower-level participants optimize generation dispatch and demand response accordingly. The bi-level model is transformed into an equivalent single-level formulation using Karush–Kuhn–Tucker conditions and solved through a hybrid particle swarm optimization–mathematical programming approach. Simulation results based on an extended IEEE 30-bus system demonstrate improved coordination, enhanced scheduling flexibility, and reduced operating costs and carbon emissions. Compared with centralized optimization, the proposed framework enables the integrated energy operator and energy supplier to achieve revenues of 3.18 × 105 CNY and 3.95 × 105 CNY, respectively, while reducing the load aggregator’s cost by 41.71%, confirming its effectiveness for coordinated low-carbon IES scheduling.

Authors

Institutions

Publication Details

Journal
Processes
Published
2026-03-11
DOI
https://doi.org/10.3390/pr14060900
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Game-Theoretic Hierarchical Optimization of Electricity–Heat–Hydrogen Energy Systems with Carbon Capture

Dandan Li, Xu Yang, Sile Hu, Jiaqiang Yang et al.
Processes
Integrated Energy Systems Optimization
article

Game-Theoretic Hierarchical Optimization of Electricity–Heat–Hydrogen Energy Systems with Carbon Capture

Dandan Li, Xu Yang, Sile Hu, Jiaqiang Yang, Yu Guo
article en

Abstract

The coupling of electricity, heat, and hydrogen subsystems together with carbon capture technologies introduces complex operational interactions in modern multi-energy systems. Existing game-based scheduling studies mainly focus on electricity–heat or electricity–heat–gas coupling, often neglecting hydrogen blending, carbon capture integration, and strategic coordination among heterogeneous stakeholders. To address these gaps, this study develops a game-theoretic hierarchical optimization framework for electricity–heat–hydrogen integrated energy systems incorporating carbon capture. Compared with conventional multi-energy game models, the proposed framework integrates hydrogen blending and carbon capture into a unified electricity–heat–hydrogen–carbon coupling structure, enabling coordinated low-carbon operation. A Stackelberg leader–follower structure is adopted, where the upper-level operator determines electricity and heat prices, and lower-level participants optimize generation dispatch and demand response accordingly. The bi-level model is transformed into an equivalent single-level formulation using Karush–Kuhn–Tucker conditions and solved through a hybrid particle swarm optimization–mathematical programming approach. Simulation results based on an extended IEEE 30-bus system demonstrate improved coordination, enhanced scheduling flexibility, and reduced operating costs and carbon emissions. Compared with centralized optimization, the proposed framework enables the integrated energy operator and energy supplier to achieve revenues of 3.18 × 105 CNY and 3.95 × 105 CNY, respectively, while reducing the load aggregator’s cost by 41.71%, confirming its effectiveness for coordinated low-carbon IES scheduling.

ProcessesVol. 14(6)
Inner Mongolia Electric Power (China) (CN), Zhejiang University (CN)
Affordable and clean energy
Openalex Percentile: Top 23%
Integrated Energy Systems Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.