Technology Applications in Sustainable Energy and Power Engineering
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 302
Special Issue Editors
Interests: hybrid electric vehicle; Zero-carbon engine; hydrogen; artificial intelligence
Interests: rotary engine; hydrogen; combustion; emissions control; ignition; sustainability; vehicle engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the context of dual carbon and sustainable development, renewable energy-related technologies are vigorously developing. The application of renewable energy has brought new challenges to current energy and power engineering. In the case of the most commonly used power machine, the internal combustion engine, the adoption of renewable energy sources such as hydrogen, ammonia, and methanol requires not only the modification of the original engine but also, more importantly, the calibration of the control strategy. Hybrid power systems can reduce overall vehicle emissions, and the use of renewable energy sources also requires the optimization of control strategies for the internal combustion engine and the power battery. With the sustainable development of artificial intelligence technology, its application in sustainable energy and power engineering is becoming increasingly widespread. Taking the field of internal combustion engines as an example, machine learning has achieved important results in fault diagnosis, intelligent calibration, and performance prediction. Machine learning combined with intelligent algorithms can also be used for the multi-objective optimization of performance and emissions. In addition, in the field of civil engineering, deep learning can also be used for predicting concrete strength.
However, in the existing research, there are various modeling methods in a certain field, and there is no unified conclusion. In response to the current situation, Sustainability aims to provide a platform for sharing research on technology applications of related technologies in sustainable energy and power engineering.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Sustainable energy management;
- Sustainable development of deep learning and machine learning models;
- The combination of sustainable energy and artificial intelligence;
- The technology applications in energy and power engineering.
Dr. Huaiyu Wang
Dr. Cheng Shi
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. Sustainability 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
- renewable energy
- sustainable power engineering
- artificial intelligence application
- sustainability
