Predicting Hvac-Based Demand Flexibility in Grid-Interactive Efficient Buildings Utilizing Deep Neural Networks
Category
Academic chapter/article/Conference paper
Language
English
Author(s)
- Italo Aldo Campodonico Avendano
- Amin Moazami
- Farzad Dadras Javan
- Behzad Najafi
Affiliation
- Norwegian University of Science and Technology
- SINTEF Community / Architectural Engineering
- Politecnico di Milano University
Year
2023Publisher
ECMS European Council for Modelling and Simulation
Book
Proceedings of the 37th ECMS International Conference on Modelling and Simulation, ECMS 2023 Florence; Italy 20 June 2023 through 23 June 2023
Issue
2023
ISBN
978-393743680-7
Page(s)
148 - 154
