Dr. Georgios Mavromatidis

Georgios Mavromatidis is the Head of Downloadthe Laboratory for Urban Energy Systemsvertical_align_bottom at DownloadEmpavertical_align_bottom, a Research Affiliate with the Group for Sustainability and Technology, and a Lecturer at the Department of Architecture (D-ARCH) of ETH Zurich. Georgios' research focuses on the development of computational energy models and analysis methods to explore how energy technology and policy can support the practical realization of urban energy transitions. For more information on Georgios' research interests, background, and publications, please visit his Downloadpersonal pagevertical_align_bottom on Empa's website.

Peer-Reviewed Journal Articles

• Ivalin Petkov, Alicia Lerbinger, Georgios Mavromatidis, Christof Knoeri, Volker H. Hoffmann, "Decarbonizing real estate portfolios considering optimal retrofit investment and policy conditions to 2050," iScience, Volume 26, Issue 5, 2023, 106619, ISSN 2589-0042, Downloaddoi:10.1016/j.isci.2023.106619vertical_align_bottom
  
• Mavromatidis, G., Petkov, I. (2021). MANGO: A novel optimization model for the long-term, multi-stage planning of decentralized multi-energy systems. Applied Energy, Volume 288, Downloaddoi:10.1016/j.apenergy.2021.116585vertical_align_bottom
  
• Thrampoulidis E., Mavromatidis G., Lucchi A., Orehounig K. (2020): A machine learning-based surrogate model to approximate optimal building retrofit solutions. Applied Energy, 281, 116024. Downloaddoi:10.1016/j.apenergy.2020.116024vertical_align_bottom
• Murray P., Marquant J. F., Niffeler M., Mavromatidis G., Orehounig K. (2020) Optimal transformation strategies for buildings, neighbourhoods and districts to reach CO2 emission reduction targets. Energy and Buildings, 207, 109569. Downloaddoi:10.1016/j.enbuild.2019.109569vertical_align_bottom
• Mavromatidis G., Orehounig K., L. Bollinger A., Hohmann M., Marquant J. F., Miglani S., Morvaj B., Murray B., Waibel C., Wang W., Carmeliet J. (2019): Ten questions concerning modeling of distributed multi-energy systems. Building and Environment, 165, 106372. Downloaddoi:10.1016/j.buildenv.2019.106372vertical_align_bottom
• Waibel C., Mavromatidis G., Evins R., Carmeliet J. (2019): A comparison of building energy optimization problems and mathematical test functions using static fitness landscape analysis. Journal of Building Performance Simulation, 12, 789-811. Downloaddoi:10.1080/19401493.2019.1671897vertical_align_bottom
  
• Gabrielli, P., Fürer, F., Mavromatidis, G. & Mazzotti, M. (2019): Robust and optimal design of multi-energy systems with seasonal storage through uncertainty analysis. Applied Energy. 238, 1192–1210. Downloaddoi:10.1016/j.apenergy.2019.01.064vertical_align_bottom
• Mavromatidis, G., Orehounig, K. & Carmeliet, J. (2018): Comparison of alternative decision-making criteria in a two-stage stochastic program for the design of distributed energy systems under uncertainty. Energy. 156, 709–724. Downloaddoi:10.1016/j.energy.2018.05.081vertical_align_bottom
• Mavromatidis, G., Orehounig, K. & Carmeliet, J. (2018): Design of distributed energy systems under uncertainty: A two-stage stochastic programming approach. Applied Energy. 222, 932–950. Downloaddoi:10.1016/j.apenergy.2018.04.019vertical_align_bottom
• Wang, D., Landolt, J., Mavromatidis, G., Orehounig, K., et al. (2018): CESAR: A bottom-up building stock modelling tool for Switzerland to address sustainable energy transformation strategies. Energy and Buildings. 169, 9–26 Downloaddoi:10.1016/j.enbuild.2018.03.020vertical_align_bottom
• Mavromatidis, G., Orehounig, K. & Carmeliet, J. (2018): A review of uncertainty characterisation approaches for the optimal design of distributed energy systems. Renewable and Sustainable Energy Reviews. 88, 258–277. Downloaddoi:10.1016/j.rser.2018.02.021vertical_align_bottom
• Mavromatidis, G., Orehounig, K. & Carmeliet, J. (2018): Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems. Applied Energy. 214, 219–238. Downloaddoi:10.1016/j.apenergy.2018.01.062vertical_align_bottom
• Wu, R., Mavromatidis, G., Orehounig, K. & Carmeliet, J. (2017): Multiobjective optimisation of energy systems and building envelope retrofit in a residential community. Applied Energy. 190, 634–649. Downloaddoi:10.1016/j.apenergy.2016.12.161vertical_align_bottom
• Mavromatidis, G., Orehounig, K., Richner, P. & Carmeliet, J. (2016): A strategy for reducing CO2 emissions from buildings with the Kaya identity – A Swiss energy system analysis and a case study. Energy Policy. 88, 343–354. Downloaddoi:10.1016/j.enpol.2015.10.037vertical_align_bottom
• Allegrini, J., Orehounig, K., Mavromatidis, G., Ruesch, F., et al. (2015): A review of modelling approaches and tools for the simulation of district-scale energy systems. Renewable and Sustainable Energy Reviews. 52, 1391–1404. Downloaddoi:10.1016/j.rser.2015.07.123vertical_align_bottom
• Mavromatidis, G., Orehounig, K. & Carmeliet, J. (2015): Evaluation of photovoltaic integration potential in a village. Solar Energy. 121, 152–168. Downloaddoi:10.1016/j.solener.2015.03.044vertical_align_bottom
• Orehounig, K., Mavromatidis, G., Evins, R., Dorer, V., et al. (2014): Towards an energy sustainable community: An energy system analysis for a village in Switzerland. Energy and Buildings. 84, 277–286. Downloaddoi:10.1016/j.enbuild.2014.08.012vertical_align_bottom
• Mavromatidis, G., Acha, S. & Shah, N. (2013): Diagnostic tools of energy performance for supermarkets using Artificial Neural Network algorithms. Energy and Buildings. 62, 304–314. Downloaddoi:10.1016/j.enbuild.2013.03.020vertical_align_bottom