Application of Artificial Intelligence for Renewable Energy Power Forecasting
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".
Deadline for manuscript submissions: 5 December 2024 | Viewed by 819
Special Issue Editors
Interests: time series analysis; short-term forecasting of electricity demand; forecasting in the time domain
Special Issues, Collections and Topics in MDPI journals
Interests: time series analysis; short-term forecasting of electricity demand; forecasting in the time domain
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Energies is running a Special Issue on the topic of the “Application of Artificial Intelligence for Renewable Energy Power Forecasting.” A new model of electricity production based on clean and renewable sources is being implemented with increasing speed in all countries. Climate change, the high prices of raw materials such as gas and oil, and conflicts in producing countries are more than enough reasons for society to direct its gaze towards clean and renewable energy production. In addition, the possibility of having small production units, even private ones, arouses even more interest in this type of generation.
However, one of the main problems that concerns this type of generation is the difficulty of making accurate predictions about the production that will be possible. These are energy sources, for example, that depend greatly on the surrounding weather conditions, among other things.
It is at this point where artificial intelligence regains special interest due to its versatility when it comes to making predictions in time series that are difficult to model.
The objective of this Special Issue is to present new emerging methodologies based on artificial intelligence and/or hybrid models in which artificial intelligence plays a determining role. Of particular interest are new methods, characterized by high uncertainty and volatility, that can help to improve decision making in current energy markets.
For this reason, we encourage researchers to submit their contributions in this field in order to advance current scientific knowledge and develop practical and/or real applications of these technologies
Dr. Óscar Trull
Prof. J. Carlos García-Díaz
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
- artificial intelligence
- forecasting
- load
- power
- renewable energy
