Machine Learning Applied in Energy Storage Systems
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D: Energy Storage and Application".
Deadline for manuscript submissions: closed (10 January 2024) | Viewed by 3492
Special Issue Editors
Interests: artificial intelligence; neural networks; genetic algorithm; echo state networks; extreme learning machines; bio-inspired computing
Special Issues, Collections and Topics in MDPI journals
Interests: electric vehicles; batteries; machine learning; fuzzy systems; control; optimization; metaheuristics; swarm intelligence
Special Issue Information
Dear Colleagues,
Energy storage is the capture of energy produced at one time for later use. Researchers from the electrical, electrochemical, chemical, thermal, and mechanical fields, among others, have performed investigations on this theme due to the importance of the topic for modern life. The current need for technologies presents challenges in optimizing and developing efficient energy storage systems.
In recent times, machine learning models have started to stand out in many fields, including energy storage systems. The main representatives of this class are Artificial Neural Networks (deep and shallow approaches), Fuzzy Systems, and nature-inspired metaheuristics (Swarm Intelligence, Evolutionary algorithms, and physical models).
In this regard, this Special Issue aims to encourage both academic and industrial researchers to present their latest findings concerning the previously cited aspects, which can significantly contribute to the achievement of new methods to develop processes or devices to improve the usage of such systems.
The authors should provide a comprehensive and scientifically sound overview of the most recent research and methodological approaches. Both experimental and methodological contributions are welcome.
The Editors of this Special Issue welcome submissions that address the following non-exhaustive list of issues:
- Machine learning;
- Artificial Neural networks;
- Fuzzy Systems;
- Nature-inspried metaheuristics;
- Convolutional neural networks;
- Deep learning;
- Feature selection;
- Clustering;
- Classification;
- Signal processing;
- Reinforced learning;
- Supervised/unsupervised learning;
- Swarm intelligence;
- Evolutionary algorithms;
- Flow battery;
- Rechargeable battery;
- Ultrabattery;
- Li-ion;
- Capacitor;
- Supercapacitor;
- Superconducting magnetic energy storage (SMES);
- Water reservoir;
- Hydrogen storage;
- Brick storage heater;
- Thermal energy storage;
- Ice storage air conditioning;
- Steam accumulator;
- Seasonal thermal energy storage;
- Compressed air energy storage (CAES);
- Flywheel energy storage;
- Gravitational potential energy;
- Hydraulic accumulator;
- Pumped-storage hydroelectricity.
Prof. Dr. Hugo Valadares Siqueira
Prof. Dr. Fernanda Cristina Corrêa
Prof. Dr. Thiago Antonini Alves
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.
