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THEMATIC TRACK: AIPES 2023 - Artificial Intelligence in Power and Energy SystemsEPIA 2023 - 22nd EPIA Conference on Artificial IntelligenceFaial Island, Azores, PortugalSeptember 5-8, 2023https://epia2023.inesctec.pt/
Dear colleagues,We would like to invite you to submit a paper to the Thematic Track on Artificial Intelligence in Power and Energy Systems (AIPES) of EPIA 2023, to be held in Faial Island, Azores, between September 5th and September 8th, 2023 (https://epia2023.inesctec.pt/).
AIPES welcomes full-length papers (of up to 12 pages) and also short papers (up to 6 pages), demonstrating practical applications. All papers should be submitted in PDF format through the EPIA 2022 EasyChair submission page.
Authors should consult Springer’s authors’ guidelines and use their proceedings templates, either for LaTeX or for Word, for the preparation of their papers. Springer encourages authors to include their ORCIDs in their papers. In addition, the corresponding author of each paper, acting on behalf of all of the authors of that paper, must complete and sign a Consent-to-Publish form. The corresponding author signing the copyright form should match the corresponding author marked on the paper. Once the files have been sent to Springer, changes relating to the authorship of the papers cannot be made.
Accepted papers will be included in the conference proceedings (a volume of Springer’s LNAI-Lecture Notes in Artificial Intelligence), provided that at least one author is registered in EPIA 2023 by the early registration deadline. EPIA 2023 proceedings are indexed in Thomson Reuters ISI Web of Science, Scopus, DBLP and Google Scholar.
The two best papers will be invited to publish an extended version in the journal Energy Informatics, Springer.
Each accepted paper must be presented by one of the authors in a track session.
The Thematic Track on Artificial Intelligence in Power and Energy Systems aims at providing an advanced discussion forum on recent and innovative work on the application of artificial intelligence approaches in the field of power and energy systems, including agent-based systems, data-mining, machine learning methodologies, forecasting and optimization.