Data-Driven Methods and Algorithms in Smart Grids
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".
Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 2001
Special Issue Editor
Special Issue Information
Dear Colleagues,
The Guest Editor is inviting submissions to a Special Issue of Energies on the subject area of ‘Data-driven methods and algorithms in Smart Grids’. Power grids are facing a new operational era characterized by cleaner power generation reflected in the exponential penetration of renewable energy sources (RESs) and the rapid expansion of transportation electrification (TE), as well as by the embedding of intelligence based on new approaches in computer and data science.
This Special Issue will deal with novel data-driven and machine learning-based techniques for the efficient operation and control of smart grids in the presence of RESs and TE.
Topics of interest for publication include, but are not limited to:
- Machine learning-based optimization and control of power systems;
- Data-driven demand-side management;
- Data analysis methods for handling uncertainties;
- Machine learning methods for the control or electric vehicles;
- Machine learning-based control of energy storage systems;
- Applications of reinforcement learning for efficient energy management;
- Applications of machine learning and data analytics for smart grid communications;
- Prediction of consumption and charging prices;
- Learning for energy markets;
- Data analytics study of interplay between smart grids and social networks;
- Comparisons between model-based and data-driven approaches;
- Combination of model-based and data-driven approaches for the management of smart grids;
- Frequency control with machine learning.
Dr. Eleni Stai
Guest Editor
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. 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
- optimization and control of smart grids
- machine learning for smart grids
- pricing schemes
- electric vehicles control
- demand-side management
- energy storage systems
- uncertainties
- energy management
- reinforcement learning
- smart grid communications
- energy markets
- frequency control
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