Applications of Machine Learning and Artificial Intelligence in Modern Power and Energy Systems, 2nd Edition
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 September 2025 | Viewed by 681
Special Issue Editors
Interests: electrical engineering; electronics; artificial intelligence; neural networks; power systems; applied mathematics; signal processing
Special Issues, Collections and Topics in MDPI journals
Interests: telecommunication networks; Internet of Things; network security
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Intelligent energy management, conversion and control are vital to optimizing the generation, distribution and consumption of electrical energy and the corresponding necessity of using solid and liquid fossil fuels. In the last several years, many research organizations and institutions around the world have made efforts towards the realization of innovative and cost-effective energy conversion and utilization. With the technological improvements in renewable energy sources (RESs), electricity production is transitioning from the traditional centralized systems to distributed energy systems.
The introduction of renewable sources and high-capacity accumulator batteries to electricity power grids, together with traditional energy sources, has led to new requirements related to prediction, coordination, conversion and control of energy flows. Along with the other utilized techniques, artificial intelligence, neural networks and machine learning are highly applicable for more efficient management, forecasting, optimization and control of smart power grids.
This Special Issue aims to collect new research information and contributions on intelligent energy management, conversion, prediction and control, including, but not limited to, smart applications for power grid control, renewable energy sources, power electronic converters, fuel cells and others.
Smart energy management and control can be effectively realized in various ways, including the following:
- Effective load prediction and management, applying machine learning, neural networks and artificial intelligence;
- Fuel consumption forecasting and optimization;
- Efficiency optimization in power flow management;
- Power electronics energy conversion with loss minimization;
- Monitoring and timely troubleshooting of intelligent energy systems;
- Energy and power system management and optimization;
- Energy and power resiliency and trust.
Prof. Dr. Valeri Mladenov
Dr. Panagiotis Sarigiannidis
Guest Editors
Manuscript Submission Information
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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. Electronics 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
- smart grid management and control
- renewable energy sources
- load forecasting
- neural networks
- artificial intelligence
- machine learning
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