Solar Radiation Prediction
A special issue of Forecasting (ISSN 2571-9394). This special issue belongs to the section "Power and Energy Forecasting".
Deadline for manuscript submissions: 31 October 2024 | Viewed by 731
Special Issue Editors
Interests: solar radiation forecasting; photovoltaic system; renewable energy; machine learning; neural networks; CPS systems; IoT; smart cities
Special Issues, Collections and Topics in MDPI journals
2. Energy Center Lab, Politecnico di Torino, 10138 Turin, Italy
Interests: co-simulation techniques; multi-energy system; smart grid; IoT infrastructure; cloud computing; machine learning; artificial intelligence
Special Issue Information
Dear Colleagues,
The critical depletion of fossil fuels and the global climate change have stimulated many countries to employ ever-larger volumes of renewable energy sources (RESs) to gradually substitute the conventional carbon-based technologies. The International Energy Agency estimates that in the coming years solar photovoltaic systems will show the fastest growth among other renewables, driven by supportive government policies and favorable market conditions.
This increasing RES employment has led several countries to develop more sophisticated smart grids. However, with the larger penetration of RESs, smart grids require further adaptations to face the challenges posed by this kind of energy source. The uncertainty of power supply affects the stability of power grids. Recent findings suggest that the problem of fluctuating power outputs can be solved by adopting smart system operating procedures such as real-time forecasting. The prediction of future energy production can significantly improve the energy management of smart grids.
In this Special Issue, we are interested in innovative solutions for the planning, analysis and optimization of solar irradiance and PV forecasting:
- Solar irradiance forecasting;
- Solar forecasting based on satellite imagery;
- NWPM solar forecasting;
- PV power forecasting;
- PV system modelling;
- Parametric and non-parametric PV models;
- Smart grid integration;
- Models for synthetic data generation;
- GIS tools for energy planning and management.
Dr. Alessandro Aliberti
Dr. Luca Barbierato
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. Forecasting is an international peer-reviewed open access quarterly 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 1800 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
- variable renewable energy
- solar irradiance forecasting
- photovoltaic forecasting
- models for synthetic data generation
- modelling and simulation tools for PV systems
- GIS tools for energy planning and management
- solar forecasting based on satellite imagery
- NWPM solar forecasting
- smart grid integration
- probabilistic forecasting as a solar resource
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