Introducing reinforcement learning to the energy system design processApplied Energy. 2020. Vol. 262, p. 114580. DOI : 10.1016/j.apenergy.2020.114580.
Self-commissioning glare-based control system for integrated venetian blind and electric lightingBuilding and Environment. 2020. Vol. 171, p. 106642. DOI : 10.1016/j.buildenv.2019.106642.
Quantifying the impacts of climate change and extreme climate events on energy systemsNature Energy. 2020. Vol. 5, p. 150-159. DOI : 10.1038/s41560-020-0558-0.
Evaluating the electricity saving potential of electrochromic glazing for cooling and lighting at the scale of the Swiss non-residential national building stock using a Monte Carlo modelEnergy. 2019. Vol. 185, p. 136-147. DOI : 10.1016/j.energy.2019.07.037.
Solar cooking potential in Switzerland: Nodal modelling and optimizationSolar Energy. 2019-12-01. Vol. 194, p. 788-803. DOI : 10.1016/j.solener.2019.10.071.
Redefining energy system flexibility for distributed energy system designApplied Energy. 2019-11-01. Vol. 253, p. 113572. DOI : 10.1016/j.apenergy.2019.113572.
Eight-month experimental study of energy impact of integrated control of sun shading and lighting system based on HDR vision sensorEnergy and Buildings. 2019-11-15. Vol. 203, p. 109443. DOI : 10.1016/j.enbuild.2019.109443.
Performance assessment of the BTDF data compression based on wavelet transforms in daylighting simulationSolar Energy. 2019-09-15. Vol. 190, p. 329-336. DOI : 10.1016/j.solener.2019.07.096.
Earlier publications can be found in Infoscience.