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Energies
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Simulation and Modeling for Low-Carbon Energy Systems
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Simulation and Modeling for Low-Carbon Energy Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".

Deadline for manuscript submissions: closed (25 April 2025) | Viewed by 1227

Special Issue Editors

Dr. Peng Wang

E-Mail Website
Guest Editor
Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
Interests: power system low-carbon planning and operation simulation; distributed optimization algorithm
Dr. Yaowang Li

E-Mail Website
Guest Editor
Institute of Low-Carbon Urban Energy System, Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu 610213, China
Interests: low-carbon power system; energy storage; power system optimization
Dr. Xu Zhou

E-Mail Website
Guest Editor
Department of Chemical Engineering, University College London, London WC1E 6BT, UK
Interests: distributed optimization; robust optimization; optimal control; game theory and its applications on energy systems

Special Issue Information

Dear Colleagues,

Under the influence of global warming, the establishment of a low-carbon energy system that is based on the high penetration of renewable resources has become an imminent necessity. The fluctuation and intermittency of such novel energy sources will profoundly alter the structure and scheduling of power systems and even energy systems as a whole. To this end, the modelling of low-carbon energy systems is crucial, as these are characterized by a high accuracy, high spatial–temporal resolution and high reliability. Moreover, the diversification of the operational modes driven by the uncertainties of novel energy sources necessitates more comprehensive simulation, complex operational optimization, and the control of low-carbon energy systems.

This Special Issue aims to present and disseminate the most recent advances related to the theory, modelling, application and control of low-carbon power systems and multi-energy systems.

The scope of this Special Issue includes, but is not limited to, the following topics:

  • All aspects of the modelling and simulation of power systems and energy systems, including the production, transformation, distribution and utilization of energy.
  • Design, theory, and methods used to plan, model and simulate power systems and energy systems.
  • Modelling and simulation based on carbon emission theory in power systems and energy systems.
  • The centralized or distributed optimization theory, design and algorithm of power systems and energy systems.
  • Advanced modelling approaches for energy systems, including data-driven methods, model-based methods, and hybrid patterns.

Dr. Peng Wang
Dr. Yaowang Li
Dr. Xu Zhou
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. Energies 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 2600 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

  • low-carbon energy system
  • operation simulation
  • modelling
  • optimization
  • carbon accounting

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Published Papers (2 papers)

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Research

18 pages, 9982 KiB  
Article
Collaborative Planning of Source–Grid–Load–Storage Considering Wind and Photovoltaic Support Capabilities
by Bin Wang, Zengyao Tian, Haotian Yang, Chunshan Li, Xingwei Xu, Shiyu Zhu, Ershun Du and Ning Zhang
Energies 2025, 18(8), 2045; https://doi.org/10.3390/en18082045 - 16 Apr 2025
Viewed by 147
Abstract
With the transformation of the global energy structure and the rapid development of new power generation technologies, new power system planning faces the challenge of multi-source–storage coordinated deployment. This paper proposes a new power system planning method, the collaborative planning of source–grid–load–storage, considering [...] Read more.
With the transformation of the global energy structure and the rapid development of new power generation technologies, new power system planning faces the challenge of multi-source–storage coordinated deployment. This paper proposes a new power system planning method, the collaborative planning of source–grid–load–storage, considering wind and photovoltaic power generation systems. First, taking into account the access of renewable energy such as wind and solar power, a renewable energy output model is constructed. Secondly, a typical intraday dispatch model of the new power system is constructed; on this basis, by adding constraints of different types of power sources, a multi-source and storage coordinated deployment planning model is constructed. Finally, through actual case studies in three provinces of Northeast China, the effectiveness of the proposed method is analyzed and verified. The results show that compared with traditional planning methods, the method proposed in this paper can significantly improve the economy and environmental friendliness of the system while meeting the requirements of power supply security. Full article
(This article belongs to the Special Issue Simulation and Modeling for Low-Carbon Energy Systems)
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16 pages, 1696 KiB  
Article
Dynamic Carbon Emission Factors in Source–Network–Storage Power System Planning: A Focus on Inverse Modelling
by Yixin Li, Weijie Wu, Haotian Yang, Guoxian Gong, Yining Zhang, Shuxin Luo, Shucan Zhou and Peng Wang
Energies 2024, 17(24), 6346; https://doi.org/10.3390/en17246346 - 17 Dec 2024
Viewed by 649
Abstract
In light of global climate change, China has set strategic goals for carbon peaking by 2030 and carbon neutrality by 2060, emphasizing the necessity of constructing a new power system with a high proportion of renewable energy sources. As coal-fired power plants are [...] Read more.
In light of global climate change, China has set strategic goals for carbon peaking by 2030 and carbon neutrality by 2060, emphasizing the necessity of constructing a new power system with a high proportion of renewable energy sources. As coal-fired power plants are the main carbon emissions source in the power system, their low-carbon transition and morphology structure optimization is crucial. This paper explores the critical role of dynamic carbon emission factors within source–network–storage power system planning and proposes an innovative inverse dynamic carbon emission factor that effectively captures the nonlinear relationship between load rates and emissions. Comparative analyses using the HRP-38 test case demonstrate that the inverse model enhances computational efficiency, reduces solution times, and more accurately reflects the emissions characteristics of coal-fired units across varying operational conditions. Furthermore, the inverse model offers improved economic performance and broader flexibility in unit selection, highlighting its potential to balance carbon emissions control and economic optimization in future power system planning. Full article
(This article belongs to the Special Issue Simulation and Modeling for Low-Carbon Energy Systems)
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