Buildings are expected to significantly contribute to the adoption of renewables, and mainly solar technologies due to largely unutilised roof space. A framework to assist the decision making process towards the optimal integration of solar energy in urban areas, with the focus on photovoltaic panels, considering spatiotemporal aspects, is presented using a village in Switzerland as a case study. Calculating the solar potential of the examined area is the first step towards determining the optimal structures to install photovoltaics. Utilisation of weather station measurements for the solar resource of a built-up area is prone to errors due to the complicated geometry of the built environment. Therefore, modelling in order to accurately determine the solar potential on a spatiotemporal scale is presented as the most promising solution. A workflow utilising Digital Elevation Models (DEM) is presented in order to create solar availability profiles for each building examined, taking into account the different surface orientations, the neighbouring structures, but also the surrounding topography. With the same techniques, the area availability for such installations is also quantified. In the next step, synthetic profiles for the electricity demand of the buildings are created taking into account the different building types. Having modelled the solar resource as well as the demand for electricity in the building stock of the examined area, the energy hub concept is employed to optimise the management of the renewable energy flows, considering multiple objectives. The energy hub output allows us to determine the optimal roof surfaces for solar installations that minimise the cost of meeting the energy demand and/or maximise the amount of solar electricity that can be used locally. Due to the intermittency of solar radiation and the temporal mismatch of solar availability and electricity demand, energy storage is also included in the energy system and its capacity is optimised to increase utilisation of solar electricity. (C) 2015 Elsevier Ltd. All rights reserved.