Artificial Intelligence for Control Applications in Power and 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 (22 May 2023) | Viewed by 1399
Special Issue Editor
Interests: power systems; smart grid; energy management; optimization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Power and energy systems are evolving with increasing Distributed Energy Resources (DERs) to ensure the demand–supply balance and cope with more volatile profiles due to renewable-based generation and new electricity usages. Typical control strategies of DERs consist in optimal decision-making processes that target technical, economical, and/or environmental criteria. Widely adopted solutions involve predictive approaches with look-ahead optimization of DERs setpoints based on systems models, which may suffer from i) vulnerability to uncertainties (i.e. forecast errors, model accuracy, and unknown system parameters) and ii) communication network and privacy concerns (especially for cloud applications). Compact controllers based on Artificial Intelligence (AI) and data-driven approaches can therefore be considered to mitigate the aforementioned shortcomings with faster computation at the local DERs level. This would entail taking advantage of the system expertise (i.e. models) in an offline training phase before deploying the controllers online.
For this Special Issue, original research articles investigating AI-based controllers for applications in power and energy systems are welcome. Considered techniques may include (but are not limited to): machine learning and supervised and reinforcement algorithms, as well as data mining/analysis (e.g. decisions tree, clustering, and regression). Specific attention will be paid to the comparison of methods with conventional approaches. The analysis of the their performances can include an evaluation of their robustness to uncertainties and/or system parameters drifting, as well as the fulfilment of critical constraints. Articles may cover applications including (but not limited to) the following:
- Energy management strategies (bulding and district).
- Distribution grid management fonctions (e.g. voltage regulation).
- Multi energy systems management.
- Energy communities.
- Energy demand management, storage, electrical vehicles, and distribution.
Dr. Rémy Rigo-Mariani
Guest Editor
Manuscript Submission Information
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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
- supervised learning
- reinforcement learning
- energy efficiency
- power system control and optimization
- distributed energy resources and smart grids
- energy storage
- electrical vehicles
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