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Advanced Forecasting Methods for Sustainable Power Grid: 2nd Edition

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: 25 September 2025 | Viewed by 31

Special Issue Editors


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Guest Editor
DIEEI—Electrical Electronic and Computer Engineering, University of Catania, 95125 Catania, Italy
Interests: photovoltaic systems; photovoltaic and solar forecasting; photovoltaic/thermal systems; floating photovoltaic systems, photovoltaic systems monitoring; fault detection in photovoltaic systems; distributed photovoltaic resources; renewable energy communities
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Special Issue Information

Dear Colleagues,

Many smart power grid systems currently deployed include various renewable energy sources, such as photovoltaic and wind energy. These renewable energy sources could have considerable impacts on power grid systems from both technical and environmental perspectives. The generated renewable energy can cause the discontinuity of energy production due to the non-programmable and unpredictable nature of renewable sources. The output of plants powered by non-programmable renewable energy sources (NPRESs) significantly changes the hourly pattern of zonal loads that need to be fulfilled by conventional generation plants. Thus, NPRESs introduce a stochastic component into the electricity demand related to the inherent variability of weather conditions, making the residual electricity load increasingly intermittent and harder to predict. As such, the rising implementation of NPRES plants results in both increasing imbalances between demand and generation and greater difficulty in building up the reserve margins needed to manage the randomness of the load while providing security and stability to the grid. For this reason, more effort has been made by the research community to establish accurate forecasting systems. This Special Issue aims to present advanced forecasting methods with applications that cover various practical challenges in sustainable power grids.

Topics to be covered in this Special Issue include, but are not limited to, the following:

  • Forecasting PV and wind power generation;
  • Energy demand forecasting;
  • Forecast models for wind speed and solar radiations;
  • Forecast models for grid connected MPPT;
  • Electric vehicle load forecasting;
  • Electricity price forecasting;
  • Forecasting techniques for smart grids;
  • Artificial intelligence and data-driven approaches;
  • The application of forecasting techniques in power systems;
  • Anomalies and faults prediction.

Dr. Cristina Ventura
Dr. Santi Agatino Rizzo
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.

Keywords

  • renewable forecasting
  • renewable energy sources
  • solar radiation forecasting
  • wind speed forecasting
  • fault detection
  • power forecasting
  • MPPT forecasting
  • artificial intelligence

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