Urban Energy Systems Laboratory
Empa - Swiss Federal Laboratories for Materials Science and Technology
Uberlandstrasse 129, CH-8600, Dübendorf, Switzerland
Tel: + 41 58 765 11 22
Fazel is a postdoctoral researcher at the Urban Energy Systems Laboratory of Empa and Lecturer for the Chair of Architecture and Building Systems at ETH Zurich. Prior to joining Empa, he was Assistant Professor of Building Physics at the University of Nottingham in Ningbo China (2018-2019). Fazel is an Architect by training (BArch) and a Building Engineer (MSc Architectural Engineering) who has developed a particular interest in data-driven models of HVAC systems. He completed his PhD studies at Politecnico di Milano, focusing on the applications of machine learning for multi-scale building energy audit.
Currently, he explores physics-based building energy modelling, uncertainty and randomness in energy systems, as well as the applications of machine learning in building energy analytics. He is also interested in reproducibility, bias, and privacy in data-driven building energy modelling.
- Dynamic CO2 Emission Model of Cities
The city of Zurich, has adopted the targets of the 2000 Watt Society, which proposes an 82% reduction in emissions by 2050 compared to 2005 levels. However, tracking progress towards these reduction targets requires consistent, reliable, and timely information on CO2 concentrations and emissions. In this project, we integrate bottom-up and top-down CO2 modelling approaches. Using a detailed building model including occupancy and heating and cooling systems, we provide better approximations of CO2 sources; particularly oil, natural gas, biomass, and district systems. This is combined with additional datasets (e.g. human activities, traffic, industrial emissions, power production) to estimate, “bottom-up” local contributions by each economic sector. Measurements of atmospheric CO2 concentrations provide independent “top-down” information. This project is a collaboration between the Urban Energy Systems and the Air Pollution / Environmental Technology Labs at Empa.
- Algorithmic Regulation and Control (ARC)
In a classical control loop, feedback is needed for a system to adjust its state and minimize its deviation from a given set point. In the building sector, such feedback mechanisms are generally weak and are rarely based on real measurements, resulting in well documented performance gaps throughout the whole life-cycle. Consequently, buildings are not constructed and operated in an optimal way. The aim of this project is to set up and evaluate high fidelity physics-based building energy models, to overcome the information gap. The project is particularly focused on improving the design and operation of HVAC controllers by using digital twins.
Doris Lima (ETH Zurich, iFA), Master thesis: A GAN-based framework for data-driven optimization programs. (2021)
Jordan Mignan (ETH Zurich, D-MAVT), Master thesis: Coupled vs. Decoupled: A study on Modelling District Heating Systems. (2020)
Alicia Lerbinger (ETH Zurich, D-MAVT), Semester project: A Python Module for Linking Energyhub and EnergyPlus Tools. (2020)
Master's thesis topics
Students interested in the following topics can send me an email describing their interests and expertise:
- Co-simulation of building and district energy systems;
- Model calibration;
- Synthetic data projection;
- Differential privacy, collaborative learning, and information leakage.