Artificial Intelligence Approach for Modeling of Renewable Energy Systems
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".
Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 10157
Special Issue Editor
Interests: machine learning; energy systems, analysis and optimization; economic energy research; power electronics and power conversion; thermodynamics
Special Issue Information
Dear Colleagues,
I am inviting you to submit a manuscript for consideration and possible publication in the Special Issue "Artificial Intelligence Approach for Modeling of Renewable Energy Systems" in Energies, an open access journal publishing relevant scientific research and studies published online monthly by MDPI. Since its launch in 2008, the journal has been indexed by the Science Citation Index Expanded, COMPENDEX, and other large databases.
The development of different energy structures, distributed energy system models, and user-active engagement capabilities promotes a rapid transition toward an energy system in which multiple energy carriers and systems synergistically interact. Achieving smart energy systems faces many challenges, necessitating novel intelligent and flexible tools. These challenges include the requirement for large data processing, professional competence, remote cooperation, and real-time monitoring for energy systems. However, due to the high volatility and unpredictability of renewable energy generation, renewable energy systems are becoming increasingly complicated. The analysis, scheduling, and control problems of future renewable energy systems will be difficult to resolve using standard model-based techniques. Electricity system operators have recently deployed smart meters and other cutting-edge sensing equipment to gather a growing number of data. This advocates the use of artificial intelligence (AI) approaches that directly learn pertinent information from a vast number of data to manage complex nonlinear problems without making assumptions or simplifying them. This Special Issue aims to demonstrate the operation of expert systems and neural networks by presenting a variety of problems in the different domains of energy engineering. This Special Issue covers the use of AI in the green transition, as well as following topics:
- AI for energy system optimization: electricity network, district heating network, district cooling network;
- AI for renewable energy generation forecasting: solar, wind, wave and tidal, hydropower, etc.;
- Reinforcement learning for power and energy systems;
- Signal processing and fault detection;
- AI for energy system integration.
Dr. Ali Khosravi
Guest Editor
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.
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