Load forecasting models are widely used to examine future electricity system. Typically, to estimate the actual and future electricity demand, these models constitute a database from different sources. Since these data are heterogeneous, the electricity demand pattern will be subjected to high uncertainties. Therefore, the effective design of renewable energy systems will be exposed to these uncertainties. For this reason, it is important to understand how the changes in the electricity demand profiles affect the modeling results in terms of system cost and electricity production mix. This paper presents a demonstration of the impact of the uncertainties on the methodology of distributed renewable energy sources and battery storage systems selection and design. This study starts with an uncertainty characterization to describe the input patterns of the energy planning model. Then, an uncertainty analysis is made to examine the model’s output variation given the uncertain patterns. A detailed case study is conducted for a distribution network. The uncertainties in the demand patterns has shown a stronger impact on the electricity supply mix than on the installed storage capacities and system costs that have shown a consistent behavior.