Intelligent Concepts for the Modelling, Optimization and Control of Smart Energy Systems

Dear Colleagues,

Energy systems are becoming more integrated and complex as a result of the low carbon transition of the economy, demanding new and intelligent concepts and methods to model, control and optimize the whole system from a holistic approach. This Special Issue calls for papers to showcase the latest progress in this area, with a focus on machine learning/AI approaches to energy system monitoring, modeling, control and management. Research papers exploring innovative applications in the decarbonization of different key sectors are particularly welcomed.

Topics of interest include, but are not limited to, the following:

1. Advanced neural network theory and algorithms, including physics-informed deep neural networks and graph neural networks and their applications in the energy and power field.
2. Advanced evolutionary computing theory and algorithms, including many objective optimization algorithms and their applications in the energy and power field.
3. Distributed computing and multi-agent systems and applications in the energy and power field.
4. Machine learning and AI applications in the production and utilization of clean and renewable power and energy resources, including fuel cells, hydrogen, solar and wind power, wave and tidal power, and biomass.
5. Industrial IoT and edge-cloud design and applications in the energy and power field.
6. Machine learning and AI applications in the development of electric vehicles, hydrogen combustion engines and equipment to support road transport decarbonization.
7. Machine learning and AI applications in power and energy operation and infrastructure development with significant utilization of renewable energy and mass roll-out of electric vehicles.
8. Machine learning and AI applications in the operation and control of distributed power generation systems including microgrids.
9. Machine learning and AI applications in the modeling, simulation and control of power electronics and power networks to support railway, port and airport terminal decarbonization.
10. Machine learning and AI applications in road management and the electricity market to support decarbonization.
11. Machine learning and AI applications in building energy management and decarbonization.
12. Machine learning and AI applications in the modeling and simulation of climate change.
13. Machine learning and AI applications in water treatment and waste management technologies.
14. Machine learning and AI applications in innovation education to support the net-zero transition.
15. Digital twin applications to support sector decarbonization.

Prof. Dr. Kang Li
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.

• intelligent concepts
• sector decarbonization
• distributed intelligence
• physics-informed deep neural networks
• microgrids
• smart grids