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Processes
Special Issues
Energy Systems Improvement, Conversion and Low-Carbon Development
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Energy Systems Improvement, Conversion and Low-Carbon Development

A Special Issue of Processes (ISSN 2227-9717) belonging to the section "Energy Systems".

Deadline for manuscript submissions: 31 March 2027 | Viewed by 1876

Editors

Dr. Guangyu Zuo

E-Mail Website
Guest Editor
College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China
Interests: polar renewable energy; polar automatic observation technology
Dr. Zening Li

E-Mail Website
Guest Editor
College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China
Interests: power system operation and control; energy management of polar energy systems; resilience enhancement of urban coupled networks
Special Issues, Collections and Topics in MDPI journals
Dr. Liwei Kou

E-Mail Website
Guest Editor
College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 310024, China
Interests: multi-energy systems; robot systems; autonomous underwater vehicles
Dr. Yaolong Bo

E-Mail Website
Guest Editor Assistant
Electrical Engineering Department, Zhejiang University, Hangzhou 310027, China
Interests: hydrogen-integrated energy systems; virtual power plants

Special Issue Information

Dear Colleagues,

Modern energy systems face the dual challenge of improving conversion efficiency and achieving deep decarbonization. While significant advances have been made in energy conversion technologies, the integration of these systems with low-carbon development pathways remains a critical research priority. This Special Issue will focus on the intersection of energy systems improvement, conversion, and low-carbon development.

This Special Issue aims to provide a platform for next-generation energy systems that are efficient, low-carbon, and cost-effective. We invite contributions that develop integrated solutions, including the following: the design and optimization of energy conversion processes (e.g., power-to-X, renewables, storage); modeling and simulation of energy system performance under different loads and supply conditions; process integration and intensification for low-carbon fuels and chemicals; and techno-economic or life-cycle analyses that assess low-carbon pathways. Both methodological advances and case studies on ways of improving energy system performance are welcome.

Dr. Guangyu Zuo
Dr. Zening Li
Dr. Liwei Kou
Guest Editors

Dr. Yaolong Bo
Guest Editor Assistant

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-anonymized 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

  • energy systems improvement
  • energy conversion
  • low-carbon development
  • process integration and intensification
  • renewable energy and storage
  • modeling and simulation
  • techno-economic and environmental assessment

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Published Papers (4 papers)

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Research

25 pages, 13423 KB  
Article
A Multi-Objective Dung Beetle Optimization-Based Optimal Scheduling Strategy for Active Distribution Networks with Large-Scale Electric Vehicle Integration
by Zesheng Hu, Kaikai Wang, Zhaorui Lu, Fei Zhao, Zhenfei Ma, Xingtao Tian and Zening Li
Processes 2026, 14(18), 2967; https://doi.org/10.3390/pr14182967 - 17 Sep 2026
Viewed by 274
Abstract
The large-scale integration of electric vehicles (EVs) can increase load fluctuations, operating costs, and security risks in active distribution networks (ADNs). To address these challenges, this study proposes a multi-objective optimal scheduling strategy based on a Multi-Objective Dung Beetle Optimization (MODBO) algorithm. A [...] Read more.
The large-scale integration of electric vehicles (EVs) can increase load fluctuations, operating costs, and security risks in active distribution networks (ADNs). To address these challenges, this study proposes a multi-objective optimal scheduling strategy based on a Multi-Objective Dung Beetle Optimization (MODBO) algorithm. A Monte Carlo simulation is first used to model stochastic EV charging behavior, followed by representative scenario selection using a minimum-distance criterion. A multi-objective scheduling model is then established considering photovoltaic utilization, ADN operating cost, system net-load variance, and voltage deviation. Case studies on a modified IEEE 33-bus system with 200 EVs show that uncoordinated charging increases the maximum load from 5672 kW to 6321 kW and raises the net-load variance to 4.15. With coordinated scheduling, the proposed method reduces the maximum load to 5672 kW and the variance to 1.29, while achieving 96.69% photovoltaic utilization and an operating cost of CNY 17,573. The results demonstrate that the proposed strategy effectively coordinates EV charging with distributed energy resources, mitigates load fluctuations, and improves the operational performance of ADNs. Full article
(This article belongs to the Special Issue Energy Systems Improvement, Conversion and Low-Carbon Development)
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24 pages, 4275 KB  
Article
Distributionally Robust Optimization Configuration of Microgrid Hybrid Energy Storage Based on Reliability
by Zhenlan Dou, Chunyan Zhang, Xichao Zhou, Rui Wang and Chuanliang Xiao
Processes 2026, 14(17), 2771; https://doi.org/10.3390/pr14172771 - 28 Aug 2026
Viewed by 451
Abstract
To improve the reliability of microgrid operation and the capability for off-grid autonomous operation, this study proposes a robust reliability-based optimal configuration method for microgrid hybrid energy storage systems. Firstly, the operational characteristics of the hydrogen energy storage system are analyzed, and combined [...] Read more.
To improve the reliability of microgrid operation and the capability for off-grid autonomous operation, this study proposes a robust reliability-based optimal configuration method for microgrid hybrid energy storage systems. Firstly, the operational characteristics of the hydrogen energy storage system are analyzed, and combined with the cooperative mechanism of the hydrogen energy storage and distributed power supply systems, the operation architecture of the microgrid electro-hydrogen coupling system is constructed. Secondly, according to the electro-hydrogen coupling characteristics and adjustment capability, a two-stage distributionally robust optimization configuration model of electro-hydrogen hybrid energy storage is constructed. In the first stage, the minimum investment and operation cost of the microgrid is the optimization goal. The optimal configuration model for the equipment capacity in the microgrid is constructed, and the distributed photovoltaic, wind turbine, battery, hydrogen storage tank, hydrogen fuel cell and electrolytic cell in the microgrid are fixed. In the second stage, according to the results of the capacity optimization configuration in the first stage, the operation reliability of the microgrid is taken as the optimization objective; 168 h is set as the operation cycle, and the extreme operation scenario for the new energy output from the microgrid is assumed to provide the capacity optimization boundary for the upper layer. Finally, the model is solved by the constraint generation algorithm and analyzed by an actual microgrid in a given area. The quantitative results demonstrate the validity of the proposed method: compared to systems without hydrogen energy storage, the duration of the continuous islanded operation is increased from approximately 302 h to 529 h (an improvement of approximately 75.2%), and the load-shedding duration is reduced from approximately 35 h to 7 h (an approximately 80% reduction). Full article
(This article belongs to the Special Issue Energy Systems Improvement, Conversion and Low-Carbon Development)
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20 pages, 1554 KB  
Article
Operational Flexibility Boundary Assessment of Electricity–Heating–Gas Virtual Power Plants Based on a Dynamic Unified Energy Circuit Model
by Xinyu Wang, Jiancheng Wang, Zhaoguang Pan, Zhongjian Song, Mingkuan Wu and Peinan Fan
Processes 2026, 14(17), 2713; https://doi.org/10.3390/pr14172713 - 25 Aug 2026
Viewed by 415
Abstract
Multi-energy virtual power plants (VPPs) aggregate electricity, heating, and natural gas resources to provide flexible regulation services to the external power grid. Their operational flexibility, however, cannot be accurately characterized using equipment capacities or single-period energy balances alone, because district heating and natural [...] Read more.
Multi-energy virtual power plants (VPPs) aggregate electricity, heating, and natural gas resources to provide flexible regulation services to the external power grid. Their operational flexibility, however, cannot be accurately characterized using equipment capacities or single-period energy balances alone, because district heating and natural gas networks introduce heat transport delays, pipeline thermal storage, pressure dynamics, and linepack effects. This paper proposes an operational flexibility boundary assessment method for electricity–heating–gas VPPs based on a dynamic energy circuit model (ECM). The frequency-domain ECM converts heating-network temperature dynamics and gas-network pressure dynamics into algebraic constraints, which are integrated with electric-network and multi-energy coupling-device constraints. The net exchange power at the point of common coupling (PCC) is used as the external flexibility interface, and the period-wise upper and lower boundaries are determined subject to network and device constraints, terminal-state recovery requirements, and an economic feasibility limit. Case studies on an electricity–heating–gas VPP demonstrate that the dynamic ECM captures the intertemporal regulation capability provided by pipeline thermal storage and gas-network linepack. Compared with the static model, the dynamic ECM exhibits consistently greater downward flexibility and comparable or lower upward flexibility in several periods, thereby correcting the underestimation of electrical absorption capability and the optimistic estimation of power-export capability caused by the static approximation. The economic feasibility constraint further excludes high-cost boundary schedules, yielding a technically feasible and economically acceptable flexibility range. Full article
(This article belongs to the Special Issue Energy Systems Improvement, Conversion and Low-Carbon Development)
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22 pages, 2387 KB  
Article
Coordinated Planning of Hybrid Energy Storage and Transmission Infrastructure for High Renewable Energy Penetration
by Kaikai Wang, Zesheng Hu, Yahong Xing, Jianxu Zhao, Jiakai Zhang and Xingtao Tian
Processes 2026, 14(16), 2559; https://doi.org/10.3390/pr14162559 - 11 Aug 2026
Viewed by 482
Abstract
Against the backdrop of increasing renewable energy penetration, distribution networks face the dual challenges of spatiotemporal mismatch between sources and loads, as well as the surging costs of physical capacity expansion. To address these issues, this paper proposes a joint planning method for [...] Read more.
Against the backdrop of increasing renewable energy penetration, distribution networks face the dual challenges of spatiotemporal mismatch between sources and loads, as well as the surging costs of physical capacity expansion. To address these issues, this paper proposes a joint planning method for distribution network expansion and hybrid energy storage (electrical, thermal, and cooling) in green power parks, aimed at enhancing renewable energy accommodation. With the objective of minimizing the total life-cycle cost, a comprehensive optimization model integrating network topology upgrades and hybrid storage capacity configuration is established, which is then formulated and solved as a Mixed-Integer Linear Programming (MILP) problem. The effectiveness of the proposed strategy is validated through simulation comparisons with traditional solely line-based expansion schemes on the standard IEEE 33-bus system. The results indicate that substituting network expansion with energy storage can significantly alleviate the hardware investment burden on the grid. Moreover, leveraging the spatiotemporal “buffer” effect of multi-energy hybrid storage and the operation mechanism of cooling-heating-power substitution, surplus photovoltaic generation is efficiently absorbed locally, maintaining a renewable energy accommodation rate consistently above 50%. Economic evaluation further confirms that this joint planning framework reduces the total life-cycle cost by 21.2% compared to conventional transmission expansion approaches. It significantly enhances the system’s flexible bidirectional regulation capabilities, providing a solid theoretical foundation for the coordinated development of networks and storage in green power parks with high renewable energy penetration. Full article
(This article belongs to the Special Issue Energy Systems Improvement, Conversion and Low-Carbon Development)
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