A realistic dataset generator for smart grid ecosystems with electric vehiclesA realistic dataset generator for smart grid ecosystems with electric vehicles Αφίσα σε Συνέδριο Conference Poster 2024-09-202022enResearch on the deployment and employment of electric vehicles (EVs) in the emerging Smart Grid, typically requires access to large datasets containing data that is rich and reliable. Such datasets are hard to come by in the wild due to various privacy and sensitivity considerations. In this paper, we design a dataset generator for large-scale EVs charging management. The generator (i) takes as input anonymized real-world datasets describing different energy generation and demand types, as well as charging profiles of EVs and corresponding trip and type information; (ii) fits a variety of machine learning models using this data as training sets; and (iii) generates new synthetic data that adheres to the same principles and relationships as the input. The generator comes complete with data smoothing and dataset summarization, visualization, and comparison abilities that users can utilize via a web-based interface; and is offered as a free-to-use tool to the research community.http://creativecommons.org/licenses/by/4.0/432–43313th ACM International Conference on Future Energy SystemsProceedings of the 13th ACM International Conference on Future Energy Systems Charalampidis Georgios Χαραλαμπιδης Γεωργιος Akasiadis Charilaos Rigas Emmanouil S. Chalkiadakis Georgios Χαλκιαδακης Γεωργιος Association for Computing Machinery (ACM) Dataset generator Electric vehicles Charging Smart grid