March 4, 2024, 5:43 a.m. | Costas Mylonas, Donata Boric, Leila Luttenberger Maric, Alexandros Tsitsanis, Eleftheria Petrianou, Magda Foti

cs.LG updates on arXiv.org arxiv.org

arXiv:2401.10726v2 Announce Type: replace-cross
Abstract: This study explores the crucial interplay between aggregators and building occupants in activating flexibility through Demand Response (DR) programs, with a keen focus on achieving robust decarbonization and fortifying the resilience of the energy system amidst the uncertainties presented by Renewable Energy Sources (RES). Firstly, it introduces a methodology of optimizing aggregated flexibility provision strategies in environments with limited data, utilizing Discrete Fourier Transformation (DFT) and clustering techniques to identify building occupant's activity patterns. Secondly, …

abstract arxiv building cs.lg cs.sy data data-driven demand eess.sy energy flexibility focus practical renewable resilience robust study through tools type

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Lead Data Scientist, Commercial Analytics

@ Checkout.com | London, United Kingdom

Data Engineer I

@ Love's Travel Stops | Oklahoma City, OK, US, 73120