Supervisor: Nahid Mohajeri / MSc student: Berenice Guiboud
Project duration: September 2015 – February 2016
Photovoltaics (PV) and solar thermal collectors are two solar technologies that can be installed on the rooftops of buildings and offer substantial emission savings. However, roof shape including positioning, orientation, and slope is among the important parameters that affect the overall performance and installation costs of solar technologies on rooftops. This project proposes a multidisciplinary approach for classification of different roof shapes, analysing the solar potential for each type of roofs, and assessing the roofs based on different characteristics in order to find out how well they receive solar energy. A combination of several methods, including geo-spatial tools to statistical and computation approach (machine learning) can be used to explore the complexity of design constraints for solar feasibility on rooftops (Figure 1).
Roof solar radiation in Geneva city (Google Earth background) and roof shape typologies