Abstract
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 language | English |
---|---|
Title of host publication | Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019 |
Place of Publication | Piscataway |
Publisher | IEEE Press |
Number of pages | 5 |
ISBN (Electronic) | 978-1-5386-8218-0 |
DOIs | |
Publication status | Published - Sept 2019 |
Event | 9th IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2019 - University POLITEHNICA, Bucharest, Romania, Bucharest, Romania Duration: 29 Sept 2019 → 2 Oct 2019 Conference number: 9 http://sites.ieee.org/isgt-europe-2019/ |
Conference
Conference | 9th IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2019 |
---|---|
Abbreviated title | ISGT Europe 2019 |
Country/Territory | Romania |
City | Bucharest |
Period | 29/09/19 → 2/10/19 |
Internet address |
Keywords
- Artificial Intelligence
- Classification
- Data analytics
- Deep learning
- Energy Prediction