Application of Machine Learning Tools for Energy Systems, 2nd Edition
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: 20 April 2026
Special Issue Editor
Interests: smart distribution network planning and operation; distributed generation; demand response; energy flexibility; power systems; modeling and simulation; inverse problems; methods of artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Following the success of the first edition of the Special Issue “Application of Machine Learning Tools for Energy Systems”, we are pleased to launch its second edition. Artificial Intelligence (AI) and Machine Learning (ML) are increasingly shaping the design, operation, and optimization of energy systems, supporting efficiency, reliability, and sustainability in the context of the global energy transition.
Recent advances such as deep learning, reinforcement learning, physics-informed neural networks (PINNs), digital twins, and foundation models are opening new opportunities for data-driven and hybrid approaches. At the same time, the adoption of explainable AI (XAI), federated learning, and edge AI is addressing critical issues of trust, privacy, and real-time control in smart energy systems.
This Special Issue seeks to collect contributions that highlight both innovative theoretical frameworks and practical implementations of AI/ML in energy applications, ranging from renewable integration and demand response to electric mobility, storage, and resilient multi-energy systems.
Topics of interest include (but are not limited to) the following:
- Energy forecasting and load/generation prediction using ML;
- AI-driven energy management and optimization algorithms;
- Digital twins, predictive maintenance, and reliability assessment;
- Reinforcement learning for flexibility, demand response, and grid stability;
- Explainable and trustworthy AI in power system operation;
- Federated and privacy-preserving ML for smart grids and IoT;
- AI for electric vehicles, V2G, and charging infrastructure;
- AI-enabled microgrids, energy communities, and multi-energy systems;
- Cybersecurity and resilience of AI-driven energy systems;
- AI for electricity markets, price forecasting, and energy trading.
We warmly invite original research, reviews, and case studies that demonstrate how AI and ML can accelerate the transition toward sustainable, intelligent energy systems.
Dr. Sara Carcangiu
Guest Editor
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
- artificial intelligence
- optimization
- prediction
- IoT
- deep learning
- machine learning
- power systems
- smart grids
- energy flexibility
- digital twins
- renewable integration
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
Related Special Issue
- Application of Machine Learning Tools for Energy System in Energies (7 articles)
