Special Issue "A Holistic Overview of the Energy Sector: From Engineering Approaches to Innovative ML Solutions"
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 (31 May 2023) | Viewed by 2805
Special Issue Editors
Interests: stochastic partial differential equations (SPDEs) in both finite and infinite dimensions; asymptotic expansion of finite/infinite integrals; interacting particle systems; random walk in random media; stochastic mean field games with applications in finance; time series analysis with applications in finance; machine learning and mathematical foundations of neural networks with applications in real markets
Special Issues, Collections and Topics in MDPI journals
Interests: stochastic partial differential equations with applications in finance; stochastic control with applications in finance/industry; theory and implementation of neural networks architectures
Special Issue Information
Dear Colleagues,
The energy sector constitutes one of the most challenging as well as continuously growing fields of research, both from an applied and theoretic point of view. In particular, the ecosystems linked to the energy sector span from engineering-oriented ones, as in the case of solar cell productions or windplants, to the fascinating developments of forecasting methods belonging to standard inferential statistics, to stochastic modeling in continuous time, and to the most recent applications of neural network approaches. Such a plethora of different tools, solutions, and methods have been revealled to be highly efficient also with respect to the financial arena, where energy-based products, such as load/consumption-based futures, as well as near-real, or even real, time energy exchanges, are gaining the attention of a continuously increasing number of big traders and practitioners.
Within previously depicted frameworks, this Special Issue would serve as a stimulating virtual room where the latest innovations can be presented, spanning from engineering-based approaches, hence also including, e.g., fault detection, electricity production forecast, predictive maintainance with regard to energy implant functioning, solar cells efficiency, etc., to mathematical methods, such as SPDE analysis of risky assets linked to energy sources and stochastic mean field game approaches to time dynamics of interacting energy sources, also considering NN methods for data analysis and provisions about energy production/consumption, particularly from the point of view of renewable resources.
Dr. Luca Di Persio
Dr. Francesco Giuseppe Cordoni
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
- Energy sector
- Finance
- Stochastic methods
- Machine learning
- Forecasting
