Optimization Scheduling of Hydrogen-Integrated Energy Systems Considering Multi-Timescale Carbon Trading Mechanisms

Jingjing Zhao, Yangyang Song () and Haocheng Fan
Additional contact information
Jingjing Zhao: College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 201399, China
Yangyang Song: College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 201399, China
Haocheng Fan: College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 201399, China

Energies, 2025, vol. 18, issue 7, 1-15

Abstract: Amidst the escalating global challenges presented by climate change, carbon trading mechanisms have become critical tools for driving reductions in carbon emissions and optimizing energy systems. However, existing carbon trading models, constrained by fixed settlement cycles, face difficulties in addressing the scheduling needs of energy systems that operate across multiple time scales. To address this challenge, this paper proposes an optimal scheduling methodology for hydrogen-encompassing integrated energy systems that incorporates a multi-time-scale carbon trading mechanism. The proposed approach dynamically optimizes the scheduling and conversion of hydrogen energy, electricity, thermal energy, and other energy forms by flexibly adjusting the carbon trading cycle. It accounts for fluctuations in energy demand and carbon emissions occurring both before and during the operational day. In the day-ahead scheduling phase, a tiered carbon transaction cost model is employed to optimize the initial scheduling framework. During the day scheduling phase, real-time data are utilized to dynamically adjust carbon quotas and emission ranges, further refining the system’s operational strategy. Through the analysis of typical case studies, this method demonstrates significant benefits in reducing carbon emission costs, enhancing energy efficiency, and improving system flexibility.

Keywords: multi-integrated energy system; carbon trading; multi-timescale; optimal dispatch form (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/1996-1073/18/7/1612/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/7/1612/ (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:7:p:1612-:d:1619054

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 ().