Collaborative learning for classification and prediction of building energy flexibility

Anil Kumar, Elena Mocanu, Muhammad Babar, Phuong Nguyen

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)
19 Downloads (Pure)


In this paper we propose an simple digital learning platform for flexible energy detection using data with fine granularity. The platform is empowered with artificially intelligent methods aiming to quantify the uncertainty of building energy consumption at building level, as well as at the aggregated level. Two major learning tasks are perform in this context: prediction and classification. Firstly, the building energy prediction with various time steps resolution are perform using methods such as Fully Connected Neural Networks (FCNN), Long short-term memory (LSTM), and Decision Trees (DT). Secondly, a Support Vector Machine (SVM) method is used to unlock the building energy flexibility by performing classification assuming three different levels of flexibility. Further on, a collaborative task is integrate within the platform to improve the multi-class classification accuracy. Through the end, we argue that this approach can be considered a solid integrated and automated basic block able to incorporate future AI models in (near) real-time to explore the benefits at the synergy between built environment and emerging smart grid technologies and applications.
Original languageEnglish
Title of host publicationProceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
Place of PublicationPiscataway
PublisherIEEE Press
Number of pages5
ISBN (Electronic)978-1-5386-8218-0
Publication statusPublished - Sept 2019
Event9th IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2019 - University POLITEHNICA, Bucharest, Romania, Bucharest, Romania
Duration: 29 Sept 20192 Oct 2019
Conference number: 9


Conference9th IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2019
Abbreviated titleISGT Europe 2019
Internet address


  • Artificial Intelligence
  • Classification
  • Data analytics
  • Deep learning
  • Energy Prediction


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