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Advances in Hydrogen Energy Systems Integration, Modeling and Optimization
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Advances in Hydrogen Energy Systems Integration, Modeling and Optimization

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

Deadline for manuscript submissions: 25 December 2025 | Viewed by 6181

Special Issue Editors

Dr. Yue Qiu

E-Mail Website
Guest Editor
School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210023, China
Interests: integrated energy system; hydrogen; energy–transportation integration
Dr. Suyang Zhou

E-Mail Website
Guest Editor
School of Electrical Engineering, Southeast University, Nanjing 210096, China
Interests: integrated energy systems; artificial intelligence; demand-side management
Dr. Shichang Cui

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: integrated energy systems; stochastic optimization; power market
Dr. Qirun Sun

E-Mail Website
Guest Editor
School of Electrical and Power Engineering, Hohai University, Nanjing 211106, China
Interests: integrated energy systems; resilience; distribution system planning

Special Issue Information

Dear Colleagues,

With the rapid global energy transition and the pursuit of carbon neutrality, hydrogen energy has emerged as a strategic clean energy carrier. It enables low- to zero-carbon emissions and links power, industry, and transportation, enhancing energy system flexibility and reliability. However, challenges remain in the efficient integration and optimization of hydrogen systems.

This Special Issue highlights advancements in hydrogen energy system integration, modeling, and optimization, fostering interdisciplinary collaboration and innovation. We invite original research contributions on topics such as the following:

- Integration and optimization of green hydrogen production and storage; 

- Multi-energy systems coupling hydrogen and renewables;

- Optimization and scheduling of hydrogen systems across timescales;

- Cross-sectoral applications in power, industry, and transportation;

- Economic evaluation and business model innovation;

- AI-driven planning and optimization of hydrogen systems.

Combining theory, simulation, and case studies, this Special Issue aims to provide insights for building efficient, economical, and secure hydrogen infrastructures, supporting a global transition toward low-carbon, intelligent, and resilient energy systems.

Dr. Yue Qiu
Dr. Suyang Zhou
Dr. Shichang Cui
Dr. Qirun Sun
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 100 words) can be sent to the Editorial Office for announcement on this website.

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 monthly 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

  • integration of hydrogen energy systems
  • multi-energy complementarity optimization
  • green hydrogen production technologies
  • low-carbon energy transition
  • applications of hydrogen energy

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

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30 pages, 1914 KB  
Article
Decarbonization of Lithium Battery Plant: A Planning Methodology Considering Manufacturing Chain Flexibilities
by Anlan Chen, Yue Qiu, Ruonan Li, Wennan Zhuang, Zhizhen Li, Peng Xia, Bo Yuan, Gang Lu, Yingxiang Wang and Suyang Zhou
Processes 2025, 13(10), 3360; https://doi.org/10.3390/pr13103360 - 20 Oct 2025
Abstract
The rising penetration of electric vehicles is driving huge demand for lithium batteries, making low-carbon manufacturing a critical objective. This goal is challenged by insufficient production scheduling flexibility and the neglect of carbon-reduction technologies. To address these challenges, this paper develops a low-carbon [...] Read more.
The rising penetration of electric vehicles is driving huge demand for lithium batteries, making low-carbon manufacturing a critical objective. This goal is challenged by insufficient production scheduling flexibility and the neglect of carbon-reduction technologies. To address these challenges, this paper develops a low-carbon planning methodology for lithium battery plant energy systems by leveraging manufacturing chain flexibilities. First, a lithium battery energy–carbon material modeling approach is developed that accounts for process production delays and intermediate product storage to capture schedulable process energy consumption patterns. A nitrogen–oxygen coupling production framework is introduced to facilitate oxygen-enriched combustion technology application, while energy recovery pathways are incorporated given the high energy consumption of the formation stage. Subsequently, a process scheduling-driven planning model for lithium battery industrial integrated energy systems (IIES) is developed. Finally, the planning model is validated through four contrasting case studies and systematically evaluated using multi-criteria decision analysis (MCDA). The results demonstrate three principal conclusions: (1) incorporating process scheduling effectively enhances process energy flexibility and reduces total system costs by 19.4%, with MCDA closeness coefficient improving from 0.257 to 0.665; (2) oxygen-enriched combustion increases maximum combustion and carbon capture (CCS) rates from 90% to 95%, reducing carbon tax to 40.5% of the baseline; (3) energy recovery on the basis of process scheduling further reduces costs and carbon emissions, with battery recovery achieving an additional 30.2% cost reduction compared to 24.1% for heat recovery, and MCDA identifies this integrated approach as the optimal solution with a closeness coefficient of 0.919. Full article
(This article belongs to the Special Issue Advances in Hydrogen Energy Systems Integration, Modeling and Optimization)
23 pages, 3488 KB  
Article
Robust Distribution System State Estimation with Physics-Constrained Heterogeneous Graph Embedding and Cross-Modal Attention
by Siyan Liu, Zhuang Tang, Bo Chai and Ziyu Zeng
Processes 2025, 13(10), 3073; https://doi.org/10.3390/pr13103073 - 25 Sep 2025
Viewed by 344
Abstract
Real-time distribution system state estimation is hampered by limited observability, frequent topology changes, and measurement errors. Neural networks can capture the nonlinear characteristics of power-grid operation through a data-driven approach that possesses important theoretical value and is promising for engineering applications. In that [...] Read more.
Real-time distribution system state estimation is hampered by limited observability, frequent topology changes, and measurement errors. Neural networks can capture the nonlinear characteristics of power-grid operation through a data-driven approach that possesses important theoretical value and is promising for engineering applications. In that context, we develop a deep learning framework that leverages General Attributed Multiplex Heterogeneous Network Embedding to explicitly encode the multiplex, heterogeneous structure of distribution networks and to support inductive learning that adapts to dynamic topology. A cross-modal attention mechanism further models fine-grained interactions between input measurements and node/edge attributes, enabling the capture of nonlinear correlations essential for accurate state estimation. To ensure physical feasibility, soft power-flow residuals are incorporated into training as a physics-constrained regularization, guiding predictions toward consistency with grid operation. Extensive studies on IEEE/CIGRE 14-, 70-, and 179-bus systems show that the proposed method surpasses conventional weighted least squares and representative neural baselines in accuracy, convergence speed, and computational efficiency while exhibiting strong robustness to measurement noise and topological uncertainty. Full article
(This article belongs to the Special Issue Advances in Hydrogen Energy Systems Integration, Modeling and Optimization)
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26 pages, 2059 KB  
Article
Integration and Development Path of Smart Grid Technology: Technology-Driven, Policy Framework and Application Challenges
by Tao Wei, Haixia Li and Junfeng Miao
Processes 2025, 13(8), 2428; https://doi.org/10.3390/pr13082428 - 31 Jul 2025
Viewed by 2587
Abstract
As a key enabling technology for energy transition, the smart grid is propelling the global power system to evolve toward greater efficiency, reliability, and sustainability. Based on the three-dimensional analysis framework of “technology–policy–application”, this study systematically sorts out the technical architecture, regional development [...] Read more.
As a key enabling technology for energy transition, the smart grid is propelling the global power system to evolve toward greater efficiency, reliability, and sustainability. Based on the three-dimensional analysis framework of “technology–policy–application”, this study systematically sorts out the technical architecture, regional development mode, and typical application scenarios of the smart grid, revealing the multi-dimensional challenges that it faces. By using the methods of literature review, cross-national case comparison, and technology–policy collaborative analysis, the differentiated paths of China, the United States, and Europe in the development of smart grids are compared, aiming to promote the integration and development of smart grid technologies. From a technical perspective, this paper proposes a collaborative framework comprising the perception layer, network layer, and decision-making layer. Additionally, it analyzes the integration pathways of critical technologies, including sensors, communication protocols, and artificial intelligence. At the policy level, by comparing the differentiated characteristics in policy orientation and market mechanisms among China, the United States, and Europe, the complementarity between government-led and market-driven approaches is pointed out. At the application level, this study validates the practical value of smart grids in optimizing energy management, enhancing power supply reliability, and promoting renewable energy consumption through case analyses in urban smart energy systems, rural electrification, and industrial sectors. Further research indicates that insufficient technical standardization, data security risks, and the lack of policy coordination are the core bottlenecks restricting the large-scale development of smart grids. This paper proposes that a new type of intelligent and resilient power system needs to be constructed through technological innovation, policy coordination, and international cooperation, providing theoretical references and practical paths for energy transition. Full article
(This article belongs to the Special Issue Advances in Hydrogen Energy Systems Integration, Modeling and Optimization)
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Review

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28 pages, 2976 KB  
Review
Catalytic Combustion Hydrogen Sensors for Vehicles: Hydrogen-Sensitive Performance Optimization Strategies and Key Technical Challenges
by Biyi Huang, Yi Wang, Chao Wang, Lijian Wang and Shubin Yan
Processes 2025, 13(8), 2384; https://doi.org/10.3390/pr13082384 - 27 Jul 2025
Viewed by 2740
Abstract
As an efficient and low-carbon renewable energy source, hydrogen plays a strategic role in the global energy transition, particularly in the transportation sector. However, the flammable and explosive nature of hydrogen makes leakage risks in enclosed environments a core challenge for the safe [...] Read more.
As an efficient and low-carbon renewable energy source, hydrogen plays a strategic role in the global energy transition, particularly in the transportation sector. However, the flammable and explosive nature of hydrogen makes leakage risks in enclosed environments a core challenge for the safe promotion of hydrogen fuel cell vehicles. Catalytic combustion sensors are ideal choices due to their high sensitivity and long lifespan. Nevertheless, they face technical bottlenecks under vehicle operational conditions, such as high-power consumption caused by elevated working temperatures, slow response rates, weak anti-interference capabilities, and catalyst poisoning. This paper systematically reviews the research status of catalytic combustion hydrogen sensors for vehicle applications, summarizes technical difficulties and development strategies from the perspectives of hydrogen-sensitive material design and integration processes, and provides theoretical references and technical guidance for the development of catalytic combustion hydrogen sensors suitable for vehicle use. Full article
(This article belongs to the Special Issue Advances in Hydrogen Energy Systems Integration, Modeling and Optimization)
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