Temporal fluctuations of the electricity grid generation composition, variability of electricity consumption in building operation over the year and of the on-site renewable energy systems are factors that should be properly considered, using high-resolution data in the building energy and environmental performance assessment. In this study a methodological framework is developed to model high-resolution electricity mixes in building operation and to assess the related energy and environmental impacts over the year, by means of a life cycle approach. For most impact categories, the imported electricity generation mixes, to meet the residual building demand, show impact variations not higher than +20 % and not lower than -38 % at seasonal and daily time compared with the annual average values. Temporal variations are even more relevant in building consumption electricity mixes, which are significantly characterized by self-consumption and show noticeable reductions compared to the annual electricity generation mix in both assessed scenarios. As an example, summer and spring energy generation mixes show the best results for climate change (0.09 kgCO2eq/kWh) compared to the annual ones, while in winter and autumn mixes the contribution to climate change overcomes the respective annual results. Both summer day-mixes contribute to climate change for about 0.12 kgCO2eq/kWh, with a reduction of nearly 30 % if compared the annual data. Conversely, in the winter daymixes the contribution to climate change is about 0.20 kgCO2eq/kWh and comes mostly from the grid. The results highlight that assessed temporal variations are significant through the year for the most assessed environmental indicators. Furthermore, the use of high-resolution electricity generation mixes allows to optimize efficiently the temporal use of electricity in buildings, in sight of energy and environmental impact reduction also thanks to the employment of life cycle oriented approaches. The results also highlight the relevance of the storage system in fulfilling periods of peak demand or low renewable generation.
