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State-of-the-Art Machine Learning Tools for 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: 25 July 2024 | Viewed by 410

Special Issue Editors

E-Mail Website
Guest Editor
Department of Computer Science, University of Verona, 37129 Verona, Italy
Interests: artificial intelligence; machine learning; computational intelligence; pattern recognition; energy management; energy saving

E-Mail Website
Guest Editor
Department of Computer Science, University of Verona, 37129 Verona, Italy
Interests: artificial intelligence; knowledge representation; machine learning; multi-agent systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are thrilled to announce a new Special Issue of the MDPI Journal “Energies” titled “State-of-the-Art Machine Learning Tools for Energy Systems”. The purpose of this Special Issue is to gather new investigations into several areas related to the usage of machine learning techniques in the broad area of energy systems. We welcome papers on topics from the following non-exclusive list:

  • Machine learning methods for energy management;
  • Artificial intelligence for energy saving;
  • Digital twin applications for energy generation and management;
  • User profiling in energy management;
  • Smart grid algorithms;
  • Edge computing, green computing and the cloud for energy applications;
  • Smart energy storage with machine learning;
  • Benchmarking and social networking for energy saving.

We welcome contributions that include system descriptions, new specific techniques for machine learning energy applications, technology shift paradigms and any novel applicative research in the fields mentioned above.

The aim of this Special Issue is to focus on the research area of machine learning for energy management as this area is developing quickly and we need to increase the number of avenues for contributions in order to elevate the debate on this topic as soon as possible.

Dr. Claudio Tomazzoli
Dr. Matteo Cristani
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.


  • machine learning
  • energy systems
  • energy production
  • energy saving

Published Papers

This special issue is now open for submission.
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