In an ever-changing world running for overall expansion and facing an unprecedented climate change, the energy transition question remains at the core of today’s—and tomorrow’s—policies. To address this question, several studies have already looked into optimized energy systems minimizing the greenhouse gas emission and the costs taking into account high renewable energies penetration and energy storage solutions. Such models rely on many parameters to represent as closely as possible the actual behaviour of the system. This paper focuses on the uncertainty of these parameters. To do so, the Polynomial Chaos Expansion method is applied to highlight and rank the parameters that have the highest influence on the model Key Performance Indicator: the total cost of the system. The outcome of this analysis points out that some parameters, as the operational cost of natural gas, have a much bigger impact. In other words, reducing the uncertainty over this cost would drastically improve the robustness of the optimum energy system.