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The increasing share of intermittent Renewable Energy Sources (iRES) in the energy mix leads to a growing need for their accurate representation in energy system models. In this paper, we analyze how the results of generation planning models are impacted by the spatial representation used to model intermittent renewable technologies. It is shown that the spatial resolution, and to a lesser extent the spatial aggregation method used in a planning model, have a significant influence on the obtained system cost. The effect is quantified in a case study of European geographical scale, by varying the spatial resolution from highly resolved (hundreds of sites) to highly aggregated (1 site). A resolution-dependency of the system cost is observed under multiple renewable generation targets, and different renewable capacity restrictions. In doing so, we highlight the importance of implementing an appropriate capacity limit, especially when a high spatial resolution is used. Additionally, basic spatial aggregation methods -to process high resolution input data- are compared. • Isolation of renewable representation effects in a stylized GEP model. • iRES resolution has a strong impact on GEP model results for Europe. • Capacity limits play an important role in this effect, especially in high resolution. • Spatial aggregation method only impacts models with low resolutions. [ABSTRACT FROM AUTHOR]