[hpc-announce] Feature Paper Invitation from Guest Editors for A topical collection in “Featured Papers in Hybrid Data-Driven and Physical Modelling for Energy Related Problems: Towards Smarter Energy Management” from Energies (Impact Factor: 3.004 (2020); 5-Year Impact
anastasija.nikiforova at lu.lv
Thu Jan 13 07:12:49 CST 2022
Currently, I am serving as a Guest Editorial for MDPI Energies (A8:Artificial Intelligence and Smart Energy) journal and in case if you are interested, I would be very glad to invite you to submit (together with your colleagues and PhD students) a paper for the Special Issue "HybridData-Driven and Physical Modelling for Energy Related Problems:Towards Smarter Energy Management<https://www.mdpi.com/journal/energies/special_issues/smarter_energy_management>"(Impact Factor:3.004 (2020); 5-Year Impact Factor: 3.085 (2020)).
Energiesis fully open access. Manuscripts are peer reviewed, and a first decision is given to authors approximately 15.9 days after submission. An Article Processing Charge (APC) of 2000 CHF currently applies to all accepted papers.
Special Issue Information:
Energy-related issues are becoming more and more relevant today, including the topic of disruptive technologies, where renewable energy is referred to as one of the 12 most significant disruptive technologies. The topic is no longer limited to energy production/generation and storage and supply as a source of energy; it is becoming broader, including the close links with the electrification of transport, including electric vehicles (smart and green transportation), industrial automation, energy storage systems, data storage and data management systems. With both being very common, and at the same time disruptive and new, energy-related issues relate to both the adaptation of well-known foundations for recent trends and the optimisation of the methods and techniques already used, as well as introducing completely new methods and developing new applications, thereby promoting open innovation and smarter living.
This Special Issue, “Hybrid Data-Driven and Physical Modelling for Energy-Related Problems: Towards Smarter Energy Management”, is looking for the most advanced and latest research and will particularly focus on advances in the field covering both data-related topics and next-generation power electronic techniques and their applications. Authors are invited to submit their original work and survey papers for publication in this Special Issue of Energies. Topics of interest for this Special Issue include, but are not limited to:
* energy management systems
* data-driven approaches to energy-related issues
* advances in energy analytic, including open data on energy, its benefits, re-uses and impact
* Big Data management in the context of energy data
* machine learning (ML) techniques
* physical modelling for energy-related problems
* disruptive technology of renewable energy
* blockchain for Internet of energy management
* the role of the “energy” within the context of Industry 4.0 and Sustainable Goals
* energy data management in the context of the internet of things (IoT)
* energy data management via distributed systems
* smart grid and microgrid
* sustainable electrical energy systems
* hybrid and electric vehicle.
The keywords for feature papers could be but not limited:
* Big Data
* data management
* disruptive technology
* electric vehicles
Further information is available on https://www.mdpi.com/journal/energies/special_issues/smarter_energy_management
If you wish to check the fit of your manuscript for this Issue prior to submission, you are welcome to send a tentative title and abstract to the editorial office Ms. Carly Liu (E-Mail: carly.liu at mdpi.com<mailto:carly.liu at mdpi.com>) and you will receive feedback shortly.
Expert of the Latvian Council of Sciences - commission of (1) Natural Sciences – Computer Science and Informatics, (2) Engineering and Technology-Electrical Engineering, Electronics, Information and Communication Technologies (ICT)
Associate member of the Latvian Open Technologies Association
University of Latvia, Faculty of Computing
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