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Processes
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Advances in Carbon-Energy Perception and Low-Carbon Optimal Energy System Operation
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Advances in Carbon-Energy Perception and Low-Carbon Optimal Energy System Operation

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Sustainable Processes".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 1425

Special Issue Editors

Dr. Qian Li

E-Mail Website
Guest Editor
School of Electrical Engineering and Information Southwest Petroleum University, Chengdu 610500，China
Interests: carbon monitoring and measurement; intelligent perception of energy and carbon in energy systems; optimization and operation of energy systems
Dr. Wei Yang

E-Mail Website
Guest Editor
School of Electrical Engineering and Information, Southwest Petroleum University, Chengdu 610500, China
Interests: integrated energy systems; comprehensive utilization of natural gas pressure energy; planning of charging and swapping facilities
Dr. Shuaijia He

E-Mail Website
Guest Editor
College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Interests: integrated energy systems; distribution systems; uncertainty optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The global pursuit of carbon neutrality is driving an urgent need for more sustainable and intelligent energy systems. Integrated energy systems that simultaneously manage multiple energy carriers—such as electricity, heat, gas, and hydrogen—require a new generation of technologies capable of accurately perceiving carbon emissions in real time and optimizing operations toward low-carbon outcomes.

This Special Issue aims to bring together cutting-edge research on carbon-energy perception, multi-scale carbon emission modeling, and low-carbon optimization in energy systems. It will provide a platform for scholars and engineers to exchange new concepts, methods, and application results that promote carbon-aware intelligent control and sustainable operation. Topics of interest for this Special Issue include, but are not limited to, the following:

  • Carbon perception technologies in energy systems;
  • Multi-scale carbon emission monitoring and analysis;
  • Energy–carbon coupling modeling and simulation;
  • Low-carbon scheduling and dispatch in multi-energy systems;
  • AI and digital twin applications for carbon-aware operation;
  • Lifecycle carbon footprint evaluation methods;
  • Data-driven carbon sensing and control strategies;
  • Application studies in oil and gas, industrial parks, and smart grids;
  • Research on policy impact and regulation for carbon optimization operation.

Dr. Qian Li
Dr. Wei Yang
Dr. Shuaijia He
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • carbon-energy perception
  • low-carbon operation
  • carbon emission modeling
  • lifecycle carbon assessment
  • energy–carbon coupling
  • smart low-carbon control

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Published Papers (3 papers)

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Research

22 pages, 6824 KB  
Article
Carbon Emission Accounting and Multi-Objective Analysis for Steel Slag Road Paving: A Case Study from Xinjiang
by Dong Liu, Litian Fan, Luyao Zhang and Xiaomin Dai
Processes 2026, 14(7), 1075; https://doi.org/10.3390/pr14071075 - 27 Mar 2026
Viewed by 283
Abstract
The large-scale accumulation of steel slag from steelmaking and the over-exploitation of natural aggregates pose significant environmental and resource challenges. Focusing on the arid-cold region of Xinjiang, China, this study proposes the use of steel slag as a substitute for natural aggregates in [...] Read more.
The large-scale accumulation of steel slag from steelmaking and the over-exploitation of natural aggregates pose significant environmental and resource challenges. Focusing on the arid-cold region of Xinjiang, China, this study proposes the use of steel slag as a substitute for natural aggregates in pavement engineering. Through experimental performance evaluation and regionalized life cycle assessment (LCA), the technical feasibility and carbon reduction potential of this application were comprehensively evaluated. Results indicate that steel slag asphalt mixtures meet or exceed specification requirements in terms of high-temperature stability, water stability, and low-temperature crack resistance. However, volume stability decreases slightly with higher steel slag content and finer particle size, necessitating pretreatment for long-term durability. A local life cycle assessment model considering regional transportation factors was applied to the G30 Luhuo Expressway project. During the materialization stage, steel slag was used to replace 30% of the natural aggregates, reducing approximately 6718 kg of carbon dioxide equivalent emissions (31.4%). This, to some extent, reduced the extraction of natural resources, saved land resources, and alleviated the problems of resource shortage and price fluctuations. Sensitivity analysis reveals a positive correlation between carbon reduction and steel slag content, while transport distance strongly influences overall benefits, with a critical threshold of about 78 km defining the effective utilization range. Furthermore, a multi-objective optimization model balancing service life, cost, and carbon reduction was developed to identify an optimal steel slag content scheme, maximizing comprehensive benefits under constrained conditions. This work confirms the technical viability of steel slag pavement in extreme climates and provides a systematic framework integrating environmental benefits and logistical constraints, supporting regional industrial synergy and promoting circular economy practices in low-carbon infrastructure. Full article
(This article belongs to the Special Issue Advances in Carbon-Energy Perception and Low-Carbon Optimal Energy System Operation)
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24 pages, 2269 KB  
Article
Coordinated Dispatch Strategy for Source-Grid-Load-Storage in Active Distribution Networks Driven by Zero-Carbon Goals
by Yutong Wu, Faju Jin, Changguo Yao, Yi Zheng, Shufang Zhou and Zhe Wu
Processes 2026, 14(5), 853; https://doi.org/10.3390/pr14050853 - 6 Mar 2026
Viewed by 426
Abstract
With the continuous advancement of the construction of new power systems, the coordinated development of source-grid-load-storage has become imperative. This paper proposes a coordinated dispatch strategy for source-grid-load-storage in active distribution networks oriented toward zero-carbon goals. First, this paper introduces the concepts of [...] Read more.
With the continuous advancement of the construction of new power systems, the coordinated development of source-grid-load-storage has become imperative. This paper proposes a coordinated dispatch strategy for source-grid-load-storage in active distribution networks oriented toward zero-carbon goals. First, this paper introduces the concepts of the green electricity index and zero-carbon pathway constraints. Building upon this foundation, a coordinated dispatch model for source-grid-load-storage in active distribution networks is constructed, aiming for optimal economic performance while considering equipment and system operational constraints. On the other hand, this paper employs Information Gap Decision Theory (IGDT) to construct uncertainty sets for renewable energy output and load demand, proposing a comprehensive deviation coefficient calculation method. This approach reduces the conservativeness of dispatch decisions while ensuring their robustness. Considering the nonlinear characteristics of the model, an improved sparrow search algorithm is adopted to enhance solution efficiency. Finally, validation using the IEEE-33 node test system demonstrates the effectiveness and feasibility of the proposed method. Full article
(This article belongs to the Special Issue Advances in Carbon-Energy Perception and Low-Carbon Optimal Energy System Operation)
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15 pages, 1652 KB  
Article
Dynamic Carbon Emissions Accounting and Uncertainty Analysis for Industrial Parks
by Yumin Chen, Xiao Shao, Yukun Guo, Xiangxi Duan, Hongli Liu, Chao Yang, Li Jiang, Yang Wei and Qian Li
Processes 2026, 14(3), 429; https://doi.org/10.3390/pr14030429 - 26 Jan 2026
Viewed by 428
Abstract
Under the “dual carbon” strategy and green energy transition, traditional static accounting models have coarse temporal granularity. These models cannot meet the needs of fine-grained management and dynamic control for industrial parks. Therefore, it is urgent to develop high-resolution dynamic accounting systems and [...] Read more.
Under the “dual carbon” strategy and green energy transition, traditional static accounting models have coarse temporal granularity. These models cannot meet the needs of fine-grained management and dynamic control for industrial parks. Therefore, it is urgent to develop high-resolution dynamic accounting systems and analyze model uncertainty. This study first defines the carbon source structure and establishes the accounting boundary for industrial parks. Second, it proposes dynamic accounting methods for both direct and indirect carbon emissions. Third, the study develops an uncertainty analysis model that considers parameter variability and error propagation. Finally, the feasibility and effectiveness of the proposed method are validated through a case study of a typical industrial park in Sichuan Province, China. The results indicate that the overall uncertainty of carbon emissions in the park is 28.9%, with electricity consumption identified as the primary driver of uncertainty (Spearman correlation coefficient of 0.986). The proposed framework effectively captures real-time emission fluctuations, providing a scientific basis for fine-grained carbon management. Full article
(This article belongs to the Special Issue Advances in Carbon-Energy Perception and Low-Carbon Optimal Energy System Operation)
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