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Calculating the heat loss coefficients for performance modelling of seasonal ice thermal storage
Allan, J., Croce, L., Dott, R., Georges, G., & Heer, P. (2022). Calculating the heat loss coefficients for performance modelling of seasonal ice thermal storage. Journal of Energy Storage, 52, 104528 (9 pp.). https://doi.org/10.1016/j.est.2022.104528
Short-lived interfaces in energy materials
Borgschulte, A., Terreni, J., Fumey, B., Sambalova, O., & Billeter, E. (2022). Short-lived interfaces in energy materials. Frontiers in Energy Research, 9, 784082 (13 pp.). https://doi.org/10.3389/fenrg.2021.784082
Comparison of online and offline deep reinforcement learning with model predictive control for thermal energy management
Brandi, S., Fiorentini, M., & Capozzoli, A. (2022). Comparison of online and offline deep reinforcement learning with model predictive control for thermal energy management. Automation in Construction, 135, 104128 (15 pp.). https://doi.org/10.1016/j.autcon.2022.104128
Physics-informed linear regression is competitive with two machine learning methods in residential building MPC
Bünning, F., Huber, B., Schalbetter, A., Aboudonia, A., Hudoba de Badyn, M., Heer, P., … Lygeros, J. (2022). Physics-informed linear regression is competitive with two machine learning methods in residential building MPC. Applied Energy, 310, 118491 (14 pp.). https://doi.org/10.1016/j.apenergy.2021.118491
Robust MPC with data-driven demand forecasting for frequency regulation with heat pumps
Bünning, F., Warrington, J., Heer, P., Smith, R. S., & Lygeros, J. (2022). Robust MPC with data-driven demand forecasting for frequency regulation with heat pumps. Control Engineering Practice, 122, 105101 (14 pp.). https://doi.org/10.1016/j.conengprac.2022.105101
Expanding urban green space with superblocks
Eggimann, S. (2022). Expanding urban green space with superblocks. Land Use Policy, 117, 106111 (9 pp.). https://doi.org/10.1016/j.landusepol.2022.106111
Spatiotemporal upscaling errors of building stock clustering for energy demand simulation
Eggimann, S., Vulic, N., Rüdisüli, M., Mutschler, R., Orehounig, K., & Sulzer, M. (2022). Spatiotemporal upscaling errors of building stock clustering for energy demand simulation. Energy and Buildings, 258, 111844 (17 pp.). https://doi.org/10.1016/j.enbuild.2022.111844
The potential of implementing superblocks for multifunctional street use in cities
Eggimann, S. (2022). The potential of implementing superblocks for multifunctional street use in cities. Nature Sustainability. https://doi.org/10.1038/s41893-022-00855-2
Enhanced gas-liquid absorption through natural convection studied by neutron imaging
Fumey, B., Borgschulte, A., Stoller, S., Fricker, R., Knechtle, R., Kaestner, A., … Baldini, L. (2022). Enhanced gas-liquid absorption through natural convection studied by neutron imaging. International Journal of Heat and Mass Transfer, 182, 121967 (11 pp.). https://doi.org/10.1016/j.ijheatmasstransfer.2021.121967
Performance and dynamics of active greywater heat recovery in buildings
Hadengue, B., Morgenroth, E., Larsen, T. A., & Baldini, L. (2022). Performance and dynamics of active greywater heat recovery in buildings. Applied Energy, 305, 117677 (13 pp.). https://doi.org/10.1016/j.apenergy.2021.117677
Distributed model predictive control of buildings and energy hubs
Lefebure, N., Khosravi, M., Hudobade Badyn, M., Bünning, F., Lygeros, J., Jones, C., & Smith, R. S. (2022). Distributed model predictive control of buildings and energy hubs. Energy and Buildings, 259, 111806 (14 pp.). https://doi.org/10.1016/j.enbuild.2021.111806
Information modelling for urban building energy simulation—a taxonomic review
Malhotra, A., Bischof, J., Nichersu, A., Häfele, K. H., Exenberger, J., Sood, D., … Schweiger, G. (2022). Information modelling for urban building energy simulation—a taxonomic review. Building and Environment, 208, 108552 (18 pp.). https://doi.org/10.1016/j.buildenv.2021.108552
MANGOret: an optimization framework for the long-term investment planning of building multi-energy system and envelope retrofits
Petkov, I., Mavromatidis, G., Knoeri, C., Allan, J., & Hoffmann, V. H. (2022). MANGOret: an optimization framework for the long-term investment planning of building multi-energy system and envelope retrofits. Applied Energy, 314, 118901 (32 pp.). https://doi.org/10.1016/j.apenergy.2022.118901
Evaluation of the impact of input uncertainty on urban building energy simulations using uncertainty and sensitivity analysis
Prataviera, E., Vivian, J., Lombardo, G., & Zarrella, A. (2022). Evaluation of the impact of input uncertainty on urban building energy simulations using uncertainty and sensitivity analysis. Applied Energy, 311, 118691 (19 pp.). https://doi.org/10.1016/j.apenergy.2022.118691
Decarbonization strategies for Switzerland considering embedded greenhouse gas emissions in electricity imports
Rüdisüli, M., Romano, E., Eggimann, S., & Patel, M. K. (2022). Decarbonization strategies for Switzerland considering embedded greenhouse gas emissions in electricity imports. Energy Policy, 162, 112794 (15 pp.). https://doi.org/10.1016/j.enpol.2022.112794
Prospective life-cycle assessment of greenhouse gas emissions of electricity-based mobility options
Rüdisüli, M., Bach, C., Bauer, C., Beloin-Saint-Pierre, D., Elber, U., Georges, G., … Teske, S. L. (2022). Prospective life-cycle assessment of greenhouse gas emissions of electricity-based mobility options. Applied Energy, 306, 118065 (20 pp.). https://doi.org/10.1016/j.apenergy.2021.118065
Opportunities for passive cooling to mitigate the impact of climate change in Switzerland
Silva, R., Eggimann, S., Fierz, L., Fiorentini, M., Orehounig, K., & Baldini, L. (2022). Opportunities for passive cooling to mitigate the impact of climate change in Switzerland. Building and Environment, 208, 108574 (19 pp.). https://doi.org/10.1016/j.buildenv.2021.108574
Data-driven control of room temperature and bidirectional EV charging using deep reinforcement learning: simulations and experiments
Svetozarevic, B., Baumann, C., Muntwiler, S., Di Natale, L., Zeilinger, M. N., & Heer, P. (2022). Data-driven control of room temperature and bidirectional EV charging using deep reinforcement learning: simulations and experiments. Applied Energy, 307, 118127 (16 pp.). https://doi.org/10.1016/j.apenergy.2021.118127
Investigation on individual and collective PV self-consumption for a fifth generation district heating network
Vivian, J., Chinello, M., Zarrella, A., & De Carli, M. (2022). Investigation on individual and collective PV self-consumption for a fifth generation district heating network. Energies, 15(3), 1022 (16 pp.). https://doi.org/10.3390/en15031022
Linked data ontology for urban scale building energy simulation
Allan, J., Fierz, L., Bollinger, A., & Orehounig, K. (2021). Linked data ontology for urban scale building energy simulation. In eSIM 2020 conference proceedings (p. (8 pp.). IBPSA.
 

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